/*
 * Copyright 1993-2024 NVIDIA Corporation.  All rights reserved.
 *
 * NOTICE TO LICENSEE:
 *
 * This source code and/or documentation ("Licensed Deliverables") are
 * subject to NVIDIA intellectual property rights under U.S. and
 * international Copyright laws.
 *
 * These Licensed Deliverables contained herein is PROPRIETARY and
 * CONFIDENTIAL to NVIDIA and is being provided under the terms and
 * conditions of a form of NVIDIA software license agreement by and
 * between NVIDIA and Licensee ("License Agreement") or electronically
 * accepted by Licensee.  Notwithstanding any terms or conditions to
 * the contrary in the License Agreement, reproduction or disclosure
 * of the Licensed Deliverables to any third party without the express
 * written consent of NVIDIA is prohibited.
 *
 * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
 * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
 * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
 * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
 * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
 * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
 * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
 * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
 * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
 * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
 * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
 * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
 * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
 * OF THESE LICENSED DELIVERABLES.
 *
 * U.S. Government End Users.  These Licensed Deliverables are a
 * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
 * 1995), consisting of "commercial computer software" and "commercial
 * computer software documentation" as such terms are used in 48
 * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
 * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
 * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
 * U.S. Government End Users acquire the Licensed Deliverables with
 * only those rights set forth herein.
 *
 * Any use of the Licensed Deliverables in individual and commercial
 * software must include, in the user documentation and internal
 * comments to the code, the above Disclaimer and U.S. Government End
 * Users Notice.
 */



#if !defined(__CUDA_RUNTIME_API_H__)
#define __CUDA_RUNTIME_API_H__

#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_RUNTIME_API_H__
#endif

/**
 * \latexonly
 * \page sync_async API synchronization behavior
 *
 * \section memcpy_sync_async_behavior Memcpy
 * The API provides memcpy/memset functions in both synchronous and asynchronous forms,
 * the latter having an \e "Async" suffix. This is a misnomer as each function
 * may exhibit synchronous or asynchronous behavior depending on the arguments
 * passed to the function. In the reference documentation, each memcpy function is
 * categorized as \e synchronous or \e asynchronous, corresponding to the definitions
 * below.
 * 
 * \subsection MemcpySynchronousBehavior Synchronous
 * 
 * <ol>
 * <li> For transfers from pageable host memory to device memory, a stream sync is performed
 * before the copy is initiated. The function will return once the pageable
 * buffer has been copied to the staging memory for DMA transfer to device memory,
 * but the DMA to final destination may not have completed.
 * 
 * <li> For transfers from pinned host memory to device memory, the function is synchronous
 * with respect to the host.
 *
 * <li> For transfers from device to either pageable or pinned host memory, the function returns
 * only once the copy has completed.
 * 
 * <li> For transfers from device memory to device memory, no host-side synchronization is
 * performed.
 *
 * <li> For transfers from any host memory to any host memory, the function is fully
 * synchronous with respect to the host.
 * </ol>
 * 
 * \subsection MemcpyAsynchronousBehavior Asynchronous
 *
 * <ol>
 * <li> For transfers between device memory and pageable host memory, the function might 
 * be synchronous with respect to host.
 *
 * <li> For transfers from any host memory to any host memory, the function is fully
 * synchronous with respect to the host.
 * 
 * <li> If pageable memory must first be staged to pinned memory, the driver may
 * synchronize with the stream and stage the copy into pinned memory.
 *
 * <li> For all other transfers, the function should be fully asynchronous.
 * </ol>
 *
 * \section memset_sync_async_behavior Memset
 * The cudaMemset functions are asynchronous with respect to the host
 * except when the target memory is pinned host memory. The \e Async
 * versions are always asynchronous with respect to the host.
 *
 * \section kernel_launch_details Kernel Launches
 * Kernel launches are asynchronous with respect to the host. Details of
 * concurrent kernel execution and data transfers can be found in the CUDA
 * Programmers Guide.
 *
 * \endlatexonly
 */

/**
 * There are two levels for the runtime API.
 *
 * The C API (<i>cuda_runtime_api.h</i>) is
 * a C-style interface that does not require compiling with \p nvcc.
 *
 * The \ref CUDART_HIGHLEVEL "C++ API" (<i>cuda_runtime.h</i>) is a
 * C++-style interface built on top of the C API. It wraps some of the
 * C API routines, using overloading, references and default arguments.
 * These wrappers can be used from C++ code and can be compiled with any C++
 * compiler. The C++ API also has some CUDA-specific wrappers that wrap
 * C API routines that deal with symbols, textures, and device functions.
 * These wrappers require the use of \p nvcc because they depend on code being
 * generated by the compiler. For example, the execution configuration syntax
 * to invoke kernels is only available in source code compiled with \p nvcc.
 */

/** CUDA Runtime API Version */
#define CUDART_VERSION  13020

#if defined(__CUDA_API_VER_MAJOR__) && defined(__CUDA_API_VER_MINOR__)
# define __CUDART_API_VERSION ((__CUDA_API_VER_MAJOR__ * 1000) + (__CUDA_API_VER_MINOR__ * 10))
#else
# define __CUDART_API_VERSION CUDART_VERSION
#endif

#ifndef __DOXYGEN_ONLY__
#include "crt/host_defines.h"
#endif
#include "builtin_types.h"

#if !defined(__CUDACC_RTC_MINIMAL__) && ((defined(__CUDACC_RDC__)  || defined(__CUDACC_EWP__) || !defined(__CUDACC_RTC__)))
#include "cuda_device_runtime_api.h"
#endif /* !defined(__CUDACC_RTC_MINIMAL__) && (defined(__CUDACC_RDC__) || defined(__CUDACC_EWP__) || !defined(__CUDACC_RTC__)) */


#ifndef __CUDACC_RTC_MINIMAL__
#if defined(CUDA_API_PER_THREAD_DEFAULT_STREAM) || defined(__CUDA_API_VERSION_INTERNAL)
    #define __CUDART_API_PER_THREAD_DEFAULT_STREAM
    #define __CUDART_API_PTDS(api) api ## _ptds
    #define __CUDART_API_PTSZ(api) api ## _ptsz
#else
    #define __CUDART_API_PTDS(api) api
    #define __CUDART_API_PTSZ(api) api
#endif




#if defined(__CUDART_API_PER_THREAD_DEFAULT_STREAM)
    #define cudaMemcpy                     __CUDART_API_PTDS(cudaMemcpy)
    #define cudaMemcpyToSymbol             __CUDART_API_PTDS(cudaMemcpyToSymbol)
    #define cudaMemcpyFromSymbol           __CUDART_API_PTDS(cudaMemcpyFromSymbol)
    #define cudaMemcpy2D                   __CUDART_API_PTDS(cudaMemcpy2D)
    #define cudaMemcpyToArray              __CUDART_API_PTDS(cudaMemcpyToArray)
    #define cudaMemcpy2DToArray            __CUDART_API_PTDS(cudaMemcpy2DToArray)
    #define cudaMemcpyFromArray            __CUDART_API_PTDS(cudaMemcpyFromArray)
    #define cudaMemcpy2DFromArray          __CUDART_API_PTDS(cudaMemcpy2DFromArray)
    #define cudaMemcpyArrayToArray         __CUDART_API_PTDS(cudaMemcpyArrayToArray)
    #define cudaMemcpy2DArrayToArray       __CUDART_API_PTDS(cudaMemcpy2DArrayToArray)
    #define cudaMemcpy3D                   __CUDART_API_PTDS(cudaMemcpy3D)
    #define cudaMemcpy3DPeer               __CUDART_API_PTDS(cudaMemcpy3DPeer)
    #define cudaMemset                     __CUDART_API_PTDS(cudaMemset)
    #define cudaMemset2D                   __CUDART_API_PTDS(cudaMemset2D)
    #define cudaMemset3D                   __CUDART_API_PTDS(cudaMemset3D)
    #define cudaGraphInstantiateWithParams __CUDART_API_PTSZ(cudaGraphInstantiateWithParams)
    #define cudaGraphUpload                __CUDART_API_PTSZ(cudaGraphUpload)
    #define cudaGraphLaunch                __CUDART_API_PTSZ(cudaGraphLaunch)
    #define cudaStreamBeginCapture         __CUDART_API_PTSZ(cudaStreamBeginCapture)
    #define cudaStreamBeginCaptureToGraph  __CUDART_API_PTSZ(cudaStreamBeginCaptureToGraph)
    #define cudaStreamEndCapture           __CUDART_API_PTSZ(cudaStreamEndCapture)
    #define cudaStreamGetCaptureInfo             __CUDART_API_PTSZ(cudaStreamGetCaptureInfo)
    #define cudaStreamUpdateCaptureDependencies  __CUDART_API_PTSZ(cudaStreamUpdateCaptureDependencies)
    #define cudaStreamIsCapturing          __CUDART_API_PTSZ(cudaStreamIsCapturing)
    #define cudaMemcpyAsync                __CUDART_API_PTSZ(cudaMemcpyAsync)
    #define cudaMemcpyToSymbolAsync        __CUDART_API_PTSZ(cudaMemcpyToSymbolAsync)
    #define cudaMemcpyFromSymbolAsync      __CUDART_API_PTSZ(cudaMemcpyFromSymbolAsync)
    #define cudaMemcpy2DAsync              __CUDART_API_PTSZ(cudaMemcpy2DAsync)
    #define cudaMemcpyToArrayAsync         __CUDART_API_PTSZ(cudaMemcpyToArrayAsync)
    #define cudaMemcpy2DToArrayAsync       __CUDART_API_PTSZ(cudaMemcpy2DToArrayAsync)
    #define cudaMemcpyFromArrayAsync       __CUDART_API_PTSZ(cudaMemcpyFromArrayAsync)
    #define cudaMemcpy2DFromArrayAsync     __CUDART_API_PTSZ(cudaMemcpy2DFromArrayAsync)
    #define cudaMemcpy3DAsync              __CUDART_API_PTSZ(cudaMemcpy3DAsync)
    #define cudaMemcpy3DPeerAsync          __CUDART_API_PTSZ(cudaMemcpy3DPeerAsync)
    #define cudaMemcpyBatchAsync           __CUDART_API_PTSZ(cudaMemcpyBatchAsync)
    #define cudaMemcpy3DBatchAsync         __CUDART_API_PTSZ(cudaMemcpy3DBatchAsync)
    #define cudaMemcpyWithAttributesAsync  __CUDART_API_PTSZ(cudaMemcpyWithAttributesAsync)
    #define cudaMemcpy3DWithAttributesAsync __CUDART_API_PTSZ(cudaMemcpy3DWithAttributesAsync)
    #define cudaMemsetAsync                __CUDART_API_PTSZ(cudaMemsetAsync)
    #define cudaMemset2DAsync              __CUDART_API_PTSZ(cudaMemset2DAsync)
    #define cudaMemset3DAsync              __CUDART_API_PTSZ(cudaMemset3DAsync)
    #define cudaStreamQuery                __CUDART_API_PTSZ(cudaStreamQuery)
    #define cudaStreamGetDevice            __CUDART_API_PTSZ(cudaStreamGetDevice)
    #define cudaStreamGetDevResource       __CUDART_API_PTSZ(cudaStreamGetDevResource)
    #define cudaStreamGetFlags             __CUDART_API_PTSZ(cudaStreamGetFlags)
    #define cudaStreamGetId                __CUDART_API_PTSZ(cudaStreamGetId)
    #define cudaStreamGetPriority          __CUDART_API_PTSZ(cudaStreamGetPriority)
    #define cudaEventRecord                __CUDART_API_PTSZ(cudaEventRecord)
    #define cudaEventRecordWithFlags       __CUDART_API_PTSZ(cudaEventRecordWithFlags)
    #define cudaStreamWaitEvent            __CUDART_API_PTSZ(cudaStreamWaitEvent)
    #define cudaStreamAddCallback          __CUDART_API_PTSZ(cudaStreamAddCallback)
    #define cudaStreamAttachMemAsync       __CUDART_API_PTSZ(cudaStreamAttachMemAsync)
    #define cudaStreamSynchronize          __CUDART_API_PTSZ(cudaStreamSynchronize)
#define cudaSignalExternalSemaphoresAsync  __CUDART_API_PTSZ(cudaSignalExternalSemaphoresAsync)
#define cudaWaitExternalSemaphoresAsync    __CUDART_API_PTSZ(cudaWaitExternalSemaphoresAsync)
    #define cudaLaunchKernel               __CUDART_API_PTSZ(cudaLaunchKernel)
    #define cudaLaunchKernelExC            __CUDART_API_PTSZ(cudaLaunchKernelExC)
    #define cudaLaunchHostFunc             __CUDART_API_PTSZ(cudaLaunchHostFunc)
    #define cudaLaunchHostFunc_v2          __CUDART_API_PTSZ(cudaLaunchHostFunc_v2)
    #define cudaMemPrefetchAsync           __CUDART_API_PTSZ(cudaMemPrefetchAsync)
    #define cudaMemPrefetchBatchAsync           __CUDART_API_PTSZ(cudaMemPrefetchBatchAsync)
    #define cudaMemDiscardBatchAsync            __CUDART_API_PTSZ(cudaMemDiscardBatchAsync)
    #define cudaMemDiscardAndPrefetchBatchAsync __CUDART_API_PTSZ(cudaMemDiscardAndPrefetchBatchAsync)
    #define cudaLaunchCooperativeKernel    __CUDART_API_PTSZ(cudaLaunchCooperativeKernel)
    #define cudaStreamCopyAttributes       __CUDART_API_PTSZ(cudaStreamCopyAttributes)
    #define cudaStreamGetAttribute         __CUDART_API_PTSZ(cudaStreamGetAttribute)
    #define cudaStreamSetAttribute         __CUDART_API_PTSZ(cudaStreamSetAttribute)
    #define cudaMallocAsync                __CUDART_API_PTSZ(cudaMallocAsync)
    #define cudaFreeAsync                  __CUDART_API_PTSZ(cudaFreeAsync)
    #define cudaMallocFromPoolAsync        __CUDART_API_PTSZ(cudaMallocFromPoolAsync)
    #define cudaGetDriverEntryPoint        __CUDART_API_PTSZ(cudaGetDriverEntryPoint)
    #define cudaGetDriverEntryPointByVersion  __CUDART_API_PTSZ(cudaGetDriverEntryPointByVersion)
#endif

#endif  /* __CUDACC_RTC_MINIMAL__ */

/** \cond impl_private */
#if !defined(__dv)

#if defined(__cplusplus)

#define __dv(v) \
        = v

#else /* __cplusplus */

#define __dv(v)

#endif /* __cplusplus */

#endif /* !__dv */
/** \endcond impl_private */

#if (defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 350))   /** Visible to SM>=3.5 and "__host__ __device__" only **/

#define CUDART_DEVICE __device__ 

#else

#define CUDART_DEVICE

#endif /** CUDART_DEVICE */

#if !defined(__CUDACC_RTC__)
#define EXCLUDE_FROM_RTC

/** \cond impl_private */
#if defined(__DOXYGEN_ONLY__) || defined(CUDA_ENABLE_DEPRECATED)
#define __CUDA_DEPRECATED
#elif defined(_MSC_VER)
#define __CUDA_DEPRECATED __declspec(deprecated)
#elif defined(__GNUC__)
#define __CUDA_DEPRECATED __attribute__((deprecated))
#else
#define __CUDA_DEPRECATED
#endif
/** \endcond impl_private */

#if defined(__cplusplus)
extern "C" {
#endif /* __cplusplus */

/**
 * \defgroup CUDART_DEVICE Device Management
 *
 * ___MANBRIEF___ device management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the device management functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Destroy all allocations and reset all state on the current device
 * in the current process.
 *
 * Explicitly destroys and cleans up all resources associated with the current
 * device in the current process. It is the caller's responsibility to ensure
 * that the resources are not accessed or passed in subsequent API calls and
 * doing so will result in undefined behavior. These resources include CUDA types
 * ::cudaStream_t, ::cudaEvent_t, ::cudaArray_t, ::cudaMipmappedArray_t, ::cudaPitchedPtr,
 * ::cudaTextureObject_t, ::cudaSurfaceObject_t, ::textureReference, ::surfaceReference,
 * ::cudaExternalMemory_t, ::cudaExternalSemaphore_t and ::cudaGraphicsResource_t.
 * These resources also include memory allocations by ::cudaMalloc, ::cudaMallocHost,
 * ::cudaMallocManaged and ::cudaMallocPitch.
 * Any subsequent API call to this device will reinitialize the device.
 *
 * Note that this function will reset the device immediately.  It is the caller's
 * responsibility to ensure that the device is not being accessed by any 
 * other host threads from the process when this function is called.
 *
 * \note ::cudaDeviceReset() will not destroy memory allocations by ::cudaMallocAsync() and
 * ::cudaMallocFromPoolAsync(). These memory allocations need to be destroyed explicitly.
 * \note If a non-primary ::CUcontext is current to the thread, ::cudaDeviceReset()
 * will destroy only the internal CUDA RT state for that ::CUcontext.
 *
 * \return
 * ::cudaSuccess
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceSynchronize
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceReset(void);

/**
 * \brief Wait for compute device to finish
 *
 * Blocks until the device has completed all preceding requested tasks.
 * ::cudaDeviceSynchronize() returns an error if one of the preceding tasks
 * has failed. If the ::cudaDeviceScheduleBlockingSync flag was set for 
 * this device, the host thread will block until the device has finished 
 * its work.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorStreamCaptureUnsupported
 * \note_device_sync_deprecated
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceReset,
 * ::cuCtxSynchronize
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceSynchronize(void);

/**
 * \brief Set resource limits
 *
 * Setting \p limit to \p value is a request by the application to update
 * the current limit maintained by the device.  The driver is free to
 * modify the requested value to meet h/w requirements (this could be
 * clamping to minimum or maximum values, rounding up to nearest element
 * size, etc).  The application can use ::cudaDeviceGetLimit() to find out
 * exactly what the limit has been set to.
 *
 * Setting each ::cudaLimit has its own specific restrictions, so each is
 * discussed here.
 *
 * - ::cudaLimitStackSize controls the stack size in bytes of each GPU thread.
 *
 * - ::cudaLimitPrintfFifoSize controls the size in bytes of the shared FIFO
 *   used by the ::printf() device system call. Setting
 *   ::cudaLimitPrintfFifoSize must not be performed after launching any kernel
 *   that uses the ::printf() device system call - in such case
 *   ::cudaErrorInvalidValue will be returned.
 *
 * - ::cudaLimitMallocHeapSize controls the size in bytes of the heap used by
 *   the ::malloc() and ::free() device system calls. Setting
 *   ::cudaLimitMallocHeapSize must not be performed after launching any kernel
 *   that uses the ::malloc() or ::free() device system calls - in such case
 *   ::cudaErrorInvalidValue will be returned.
 *
 * - ::cudaLimitDevRuntimeSyncDepth controls the maximum nesting depth of a
 *   grid at which a thread can safely call ::cudaDeviceSynchronize(). Setting
 *   this limit must be performed before any launch of a kernel that uses the
 *   device runtime and calls ::cudaDeviceSynchronize() above the default sync
 *   depth, two levels of grids. Calls to ::cudaDeviceSynchronize() will fail
 *   with error code ::cudaErrorSyncDepthExceeded if the limitation is
 *   violated. This limit can be set smaller than the default or up the maximum
 *   launch depth of 24. When setting this limit, keep in mind that additional
 *   levels of sync depth require the runtime to reserve large amounts of
 *   device memory which can no longer be used for user allocations. If these
 *   reservations of device memory fail, ::cudaDeviceSetLimit will return
 *   ::cudaErrorMemoryAllocation, and the limit can be reset to a lower value.
 *   This limit is only applicable to devices of compute capability < 9.0.
 *   Attempting to set this limit on devices of other compute capability will
 *   results in error ::cudaErrorUnsupportedLimit being returned.
 *
 * - ::cudaLimitDevRuntimePendingLaunchCount controls the maximum number of
 *   outstanding device runtime launches that can be made from the current
 *   device. A grid is outstanding from the point of launch up until the grid
 *   is known to have been completed. Device runtime launches which violate
 *   this limitation fail and return ::cudaErrorLaunchPendingCountExceeded when
 *   ::cudaGetLastError() is called after launch. If more pending launches than
 *   the default (2048 launches) are needed for a module using the device
 *   runtime, this limit can be increased. Keep in mind that being able to
 *   sustain additional pending launches will require the runtime to reserve
 *   larger amounts of device memory upfront which can no longer be used for
 *   allocations. If these reservations fail, ::cudaDeviceSetLimit will return
 *   ::cudaErrorMemoryAllocation, and the limit can be reset to a lower value.
 *   This limit is only applicable to devices of compute capability 3.5 and
 *   higher. Attempting to set this limit on devices of compute capability less
 *   than 3.5 will result in the error ::cudaErrorUnsupportedLimit being
 *   returned.
 *
 * - ::cudaLimitMaxL2FetchGranularity controls the L2 cache fetch granularity.
 *   Values can range from 0B to 128B. This is purely a performance hint and
 *   it can be ignored or clamped depending on the platform.
 *
 * - ::cudaLimitPersistingL2CacheSize controls size in bytes available
 *   for persisting L2 cache. This is purely a performance hint and it
 *   can be ignored or clamped depending on the platform.
 *
 * \param limit - Limit to set
 * \param value - Size of limit
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorUnsupportedLimit,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceGetLimit,
 * ::cuCtxSetLimit
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceSetLimit(enum cudaLimit limit, size_t value);

/**
 * \brief Return resource limits
 *
 * Returns in \p *pValue the current size of \p limit. The following ::cudaLimit values are supported.
 * - ::cudaLimitStackSize is the stack size in bytes of each GPU thread.
 * - ::cudaLimitPrintfFifoSize is the size in bytes of the shared FIFO used by the
 *   ::printf() device system call.
 * - ::cudaLimitMallocHeapSize is the size in bytes of the heap used by the
 *   ::malloc() and ::free() device system calls.
 * - ::cudaLimitDevRuntimeSyncDepth is the maximum grid depth at which a
 *   thread can isssue the device runtime call ::cudaDeviceSynchronize()
 *   to wait on child grid launches to complete. This functionality is removed
 *   for devices of compute capability >= 9.0, and hence will return error
 *   ::cudaErrorUnsupportedLimit on such devices.
 * - ::cudaLimitDevRuntimePendingLaunchCount is the maximum number of outstanding
 *   device runtime launches.
 * - ::cudaLimitMaxL2FetchGranularity is the L2 cache fetch granularity.
 * - ::cudaLimitPersistingL2CacheSize is the persisting L2 cache size in bytes.
 *
 * \param limit  - Limit to query
 * \param pValue - Returned size of the limit
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorUnsupportedLimit,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceSetLimit,
 * ::cuCtxGetLimit
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetLimit(size_t *pValue, enum cudaLimit limit);

/**
 * \brief Returns the maximum number of elements allocatable in a 1D linear texture for a given element size.
 *
 * Returns in \p maxWidthInElements the maximum number of elements allocatable in a 1D linear texture
 * for given format descriptor \p fmtDesc.
 *
 * \param maxWidthInElements    - Returns maximum number of texture elements allocatable for given \p fmtDesc.
 * \param fmtDesc               - Texture format description.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorUnsupportedLimit,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuDeviceGetTexture1DLinearMaxWidth
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetTexture1DLinearMaxWidth(size_t *maxWidthInElements, const struct cudaChannelFormatDesc *fmtDesc, int device);
#endif

/**
 * \brief Returns the preferred cache configuration for the current device.
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this returns through \p pCacheConfig the preferred cache
 * configuration for the current device. This is only a preference. The
 * runtime will use the requested configuration if possible, but it is free to
 * choose a different configuration if required to execute functions.
 *
 * This will return a \p pCacheConfig of ::cudaFuncCachePreferNone on devices
 * where the size of the L1 cache and shared memory are fixed.
 *
 * The supported cache configurations are:
 * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default)
 * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache
 * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory
 * - ::cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory
 *
 * \param pCacheConfig - Returned cache configuration
 *
 * \return
 * ::cudaSuccess
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceSetCacheConfig,
 * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)",
 * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)",
 * ::cuCtxGetCacheConfig
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetCacheConfig(enum cudaFuncCache *pCacheConfig);

/**
 * \brief Returns numerical values that correspond to the least and
 * greatest stream priorities.
 *
 * Returns in \p *leastPriority and \p *greatestPriority the numerical values that correspond
 * to the least and greatest stream priorities respectively. Stream priorities
 * follow a convention where lower numbers imply greater priorities. The range of
 * meaningful stream priorities is given by [\p *greatestPriority, \p *leastPriority].
 * If the user attempts to create a stream with a priority value that is
 * outside the the meaningful range as specified by this API, the priority is
 * automatically clamped down or up to either \p *leastPriority or \p *greatestPriority
 * respectively. See ::cudaStreamCreateWithPriority for details on creating a
 * priority stream.
 * A NULL may be passed in for \p *leastPriority or \p *greatestPriority if the value
 * is not desired.
 *
 * This function will return '0' in both \p *leastPriority and \p *greatestPriority if
 * the current context's device does not support stream priorities
 * (see ::cudaDeviceGetAttribute).
 *
 * \param leastPriority    - Pointer to an int in which the numerical value for least
 *                           stream priority is returned
 * \param greatestPriority - Pointer to an int in which the numerical value for greatest
 *                           stream priority is returned
 *
 * \return
 * ::cudaSuccess
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreateWithPriority,
 * ::cudaStreamGetPriority,
 * ::cuCtxGetStreamPriorityRange
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetStreamPriorityRange(int *leastPriority, int *greatestPriority);

/**
 * \brief Sets the preferred cache configuration for the current device.
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this sets through \p cacheConfig the preferred cache
 * configuration for the current device. This is only a preference. The
 * runtime will use the requested configuration if possible, but it is free to
 * choose a different configuration if required to execute the function. Any
 * function preference set via
 * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)"
 * or
 * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)"
 * will be preferred over this device-wide setting. Setting the device-wide
 * cache configuration to ::cudaFuncCachePreferNone will cause subsequent
 * kernel launches to prefer to not change the cache configuration unless
 * required to launch the kernel.
 *
 * This setting does nothing on devices where the size of the L1 cache and
 * shared memory are fixed.
 *
 * Launching a kernel with a different preference than the most recent
 * preference setting may insert a device-side synchronization point.
 *
 * The supported cache configurations are:
 * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default)
 * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache
 * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory
 * - ::cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory
 *
 * \param cacheConfig - Requested cache configuration
 *
 * \return
 * ::cudaSuccess
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceGetCacheConfig,
 * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)",
 * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)",
 * ::cuCtxSetCacheConfig
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceSetCacheConfig(enum cudaFuncCache cacheConfig);

/**
 * \brief Returns a handle to a compute device
 *
 * Returns in \p *device a device ordinal given a PCI bus ID string.
 *
 * \param device   - Returned device ordinal
 *
 * \param pciBusId - String in one of the following forms: 
 * [domain]:[bus]:[device].[function]
 * [domain]:[bus]:[device]
 * [bus]:[device].[function]
 * where \p domain, \p bus, \p device, and \p function are all hexadecimal values
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceGetPCIBusId,
 * ::cuDeviceGetByPCIBusId
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetByPCIBusId(int *device, const char *pciBusId);

/**
 * \brief Returns a PCI Bus Id string for the device
 *
 * Returns an ASCII string identifying the device \p dev in the NULL-terminated
 * string pointed to by \p pciBusId. \p len specifies the maximum length of the
 * string that may be returned.
 *
 * \param pciBusId - Returned identifier string for the device in the following format
 * [domain]:[bus]:[device].[function]
 * where \p domain, \p bus, \p device, and \p function are all hexadecimal values.
 * pciBusId should be large enough to store 13 characters including the NULL-terminator.
 *
 * \param len      - Maximum length of string to store in \p name
 *
 * \param device   - Device to get identifier string for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceGetByPCIBusId,
 * ::cuDeviceGetPCIBusId
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetPCIBusId(char *pciBusId, int len, int device);

/**
 * \brief Gets an interprocess handle for a previously allocated event
 *
 * Takes as input a previously allocated event. This event must have been 
 * created with the ::cudaEventInterprocess and ::cudaEventDisableTiming
 * flags set. This opaque handle may be copied into other processes and
 * opened with ::cudaIpcOpenEventHandle to allow efficient hardware
 * synchronization between GPU work in different processes.
 *
 * After the event has been been opened in the importing process, 
 * ::cudaEventRecord, ::cudaEventSynchronize, ::cudaStreamWaitEvent and 
 * ::cudaEventQuery may be used in either process. Performing operations 
 * on the imported event after the exported event has been freed 
 * with ::cudaEventDestroy will result in undefined behavior.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport
 *
 * \param handle - Pointer to a user allocated cudaIpcEventHandle
 *                    in which to return the opaque event handle
 * \param event   - Event allocated with ::cudaEventInterprocess and 
 *                    ::cudaEventDisableTiming flags.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorMapBufferObjectFailed,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaEventCreate,
 * ::cudaEventDestroy,
 * ::cudaEventSynchronize,
 * ::cudaEventQuery,
 * ::cudaStreamWaitEvent,
 * ::cudaIpcOpenEventHandle,
 * ::cudaIpcGetMemHandle,
 * ::cudaIpcOpenMemHandle,
 * ::cudaIpcCloseMemHandle,
 * ::cuIpcGetEventHandle
 */
extern __host__ cudaError_t CUDARTAPI cudaIpcGetEventHandle(cudaIpcEventHandle_t *handle, cudaEvent_t event);

/**
 * \brief Opens an interprocess event handle for use in the current process
 *
 * Opens an interprocess event handle exported from another process with 
 * ::cudaIpcGetEventHandle. This function returns a ::cudaEvent_t that behaves like 
 * a locally created event with the ::cudaEventDisableTiming flag specified. 
 * This event must be freed with ::cudaEventDestroy.
 *
 * Performing operations on the imported event after the exported event has 
 * been freed with ::cudaEventDestroy will result in undefined behavior.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport
 *
 * \param event - Returns the imported event
 * \param handle  - Interprocess handle to open
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorMapBufferObjectFailed,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorDeviceUninitialized
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaEventCreate,
 * ::cudaEventDestroy,
 * ::cudaEventSynchronize,
 * ::cudaEventQuery,
 * ::cudaStreamWaitEvent,
 * ::cudaIpcGetEventHandle,
 * ::cudaIpcGetMemHandle,
 * ::cudaIpcOpenMemHandle,
 * ::cudaIpcCloseMemHandle,
 * ::cuIpcOpenEventHandle
 */
extern __host__ cudaError_t CUDARTAPI cudaIpcOpenEventHandle(cudaEvent_t *event, cudaIpcEventHandle_t handle);

/**
 * \brief Gets an interprocess memory handle for an existing device memory
 *          allocation
 *
 * Takes a pointer to the base of an existing device memory allocation created 
 * with ::cudaMalloc and exports it for use in another process. This is a 
 * lightweight operation and may be called multiple times on an allocation
 * without adverse effects. 
 *
 * If a region of memory is freed with ::cudaFree and a subsequent call
 * to ::cudaMalloc returns memory with the same device address,
 * ::cudaIpcGetMemHandle will return a unique handle for the
 * new memory. 
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport
 *
 * \param handle - Pointer to user allocated ::cudaIpcMemHandle to return
 *                    the handle in.
 * \param devPtr - Base pointer to previously allocated device memory 
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorMapBufferObjectFailed,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMalloc,
 * ::cudaFree,
 * ::cudaIpcGetEventHandle,
 * ::cudaIpcOpenEventHandle,
 * ::cudaIpcOpenMemHandle,
 * ::cudaIpcCloseMemHandle,
 * ::cuIpcGetMemHandle
 */
extern __host__ cudaError_t CUDARTAPI cudaIpcGetMemHandle(cudaIpcMemHandle_t *handle, void *devPtr);

/**
 * \brief Opens an interprocess memory handle exported from another process
 *          and returns a device pointer usable in the local process.
 *
 * Maps memory exported from another process with ::cudaIpcGetMemHandle into
 * the current device address space. For contexts on different devices 
 * ::cudaIpcOpenMemHandle can attempt to enable peer access between the
 * devices as if the user called ::cudaDeviceEnablePeerAccess. This behavior is 
 * controlled by the ::cudaIpcMemLazyEnablePeerAccess flag. 
 * ::cudaDeviceCanAccessPeer can determine if a mapping is possible.
 *
 * ::cudaIpcOpenMemHandle can open handles to devices that may not be visible
 * in the process calling the API.
 *
 * Contexts that may open ::cudaIpcMemHandles are restricted in the following way.
 * ::cudaIpcMemHandles from each device in a given process may only be opened 
 * by one context per device per other process.
 *
 * If the memory handle has already been opened by the current context, the
 * reference count on the handle is incremented by 1 and the existing device pointer
 * is returned.
 *
 * Memory returned from ::cudaIpcOpenMemHandle must be freed with
 * ::cudaIpcCloseMemHandle.
 *
 * Calling ::cudaFree on an exported memory region before calling
 * ::cudaIpcCloseMemHandle in the importing context will result in undefined
 * behavior.
 * 
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport
 *
 * \param devPtr - Returned device pointer
 * \param handle - ::cudaIpcMemHandle to open
 * \param flags  - Flags for this operation. Must be specified as ::cudaIpcMemLazyEnablePeerAccess
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorMapBufferObjectFailed,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorDeviceUninitialized,
 * ::cudaErrorTooManyPeers,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \note No guarantees are made about the address returned in \p *devPtr.  
 * In particular, multiple processes may not receive the same address for the same \p handle.
 *
 * \sa
 * ::cudaMalloc,
 * ::cudaFree,
 * ::cudaIpcGetEventHandle,
 * ::cudaIpcOpenEventHandle,
 * ::cudaIpcGetMemHandle,
 * ::cudaIpcCloseMemHandle,
 * ::cudaDeviceEnablePeerAccess,
 * ::cudaDeviceCanAccessPeer,
 * ::cuIpcOpenMemHandle
 */
extern __host__ cudaError_t CUDARTAPI cudaIpcOpenMemHandle(void **devPtr, cudaIpcMemHandle_t handle, unsigned int flags);

/**
 * \brief Attempts to close memory mapped with cudaIpcOpenMemHandle
 * 
 * Decrements the reference count of the memory returnd by ::cudaIpcOpenMemHandle by 1.
 * When the reference count reaches 0, this API unmaps the memory. The original allocation
 * in the exporting process as well as imported mappings in other processes
 * will be unaffected.
 *
 * Any resources used to enable peer access will be freed if this is the
 * last mapping using them.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport
 *
 * \param devPtr - Device pointer returned by ::cudaIpcOpenMemHandle
 * 
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorMapBufferObjectFailed,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMalloc,
 * ::cudaFree,
 * ::cudaIpcGetEventHandle,
 * ::cudaIpcOpenEventHandle,
 * ::cudaIpcGetMemHandle,
 * ::cudaIpcOpenMemHandle,
 * ::cuIpcCloseMemHandle
 */
extern __host__ cudaError_t CUDARTAPI cudaIpcCloseMemHandle(void *devPtr);

/**
 * \brief Blocks until remote writes are visible to the specified scope
 *
 * Blocks until remote writes to the target context via mappings created
 * through GPUDirect RDMA APIs, like nvidia_p2p_get_pages (see
 * https://docs.nvidia.com/cuda/gpudirect-rdma for more information), are
 * visible to the specified scope.
 *
 * If the scope equals or lies within the scope indicated by
 * ::cudaDevAttrGPUDirectRDMAWritesOrdering, the call will be a no-op and
 * can be safely omitted for performance. This can be determined by
 * comparing the numerical values between the two enums, with smaller
 * scopes having smaller values.
 *
 * Users may query support for this API via ::cudaDevAttrGPUDirectRDMAFlushWritesOptions.
 *
 * \param target - The target of the operation, see cudaFlushGPUDirectRDMAWritesTarget
 * \param scope  - The scope of the operation, see cudaFlushGPUDirectRDMAWritesScope
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotSupported,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuFlushGPUDirectRDMAWrites
 */
#if __CUDART_API_VERSION >= 11030
extern __host__ cudaError_t CUDARTAPI cudaDeviceFlushGPUDirectRDMAWrites(enum cudaFlushGPUDirectRDMAWritesTarget target, enum cudaFlushGPUDirectRDMAWritesScope scope);
#endif

/**
* \brief Registers a callback function to receive async notifications
*
* Registers \p callbackFunc to receive async notifications.
*
* The \p userData parameter is passed to the callback function at async notification time.
* Likewise, \p callback is also passed to the callback function to distinguish between
* multiple registered callbacks.
*
* The callback function being registered should be designed to return quickly (~10ms).
* Any long running tasks should be queued for execution on an application thread.
*
* Callbacks may not call cudaDeviceRegisterAsyncNotification or cudaDeviceUnregisterAsyncNotification.
* Doing so will result in ::cudaErrorNotPermitted. Async notification callbacks execute
* in an undefined order and may be serialized.
*
* Returns in \p *callback a handle representing the registered callback instance.
*
* \param device - The device on which to register the callback
* \param callbackFunc - The function to register as a callback
* \param userData - A generic pointer to user data. This is passed into the callback function.
* \param callback - A handle representing the registered callback instance
*
* \return
* ::cudaSuccess
* ::cudaErrorNotSupported
* ::cudaErrorInvalidDevice
* ::cudaErrorInvalidValue
* ::cudaErrorNotPermitted
* ::cudaErrorUnknown
* \notefnerr
*
* \sa
* ::cudaDeviceUnregisterAsyncNotification
*/
extern __host__ cudaError_t CUDARTAPI cudaDeviceRegisterAsyncNotification(int device, cudaAsyncCallback callbackFunc, void* userData, cudaAsyncCallbackHandle_t* callback);

/**
* \brief Unregisters an async notification callback
*
* Unregisters \p callback so that the corresponding callback function will stop receiving
* async notifications.
*
* \param device - The device from which to remove \p callback.
* \param callback - The callback instance to unregister from receiving async notifications.
*
* \return
* ::cudaSuccess
* ::cudaErrorNotSupported
* ::cudaErrorInvalidDevice
* ::cudaErrorInvalidValue
* ::cudaErrorNotPermitted
* ::cudaErrorUnknown
* \notefnerr
*
* \sa
* ::cudaDeviceRegisterAsyncNotification
*/
extern __host__ cudaError_t CUDARTAPI cudaDeviceUnregisterAsyncNotification(int device, cudaAsyncCallbackHandle_t callback);

/** @} */ /* END CUDART_DEVICE */

/**
 * \defgroup CUDART_DEVICE_DEPRECATED Device Management [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated device management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the deprecated device management functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Returns the shared memory configuration for the current device.
 *
 * \deprecated
 *
 * This function will return in \p pConfig the current size of shared memory banks
 * on the current device. On devices with configurable shared memory banks, 
 * ::cudaDeviceSetSharedMemConfig can be used to change this setting, so that all 
 * subsequent kernel launches will by default use the new bank size. When 
 * ::cudaDeviceGetSharedMemConfig is called on devices without configurable shared 
 * memory, it will return the fixed bank size of the hardware.
 *
 * The returned bank configurations can be either:
 * - ::cudaSharedMemBankSizeFourByte - shared memory bank width is four bytes.
 * - ::cudaSharedMemBankSizeEightByte - shared memory bank width is eight bytes.
 *
 * \param pConfig - Returned cache configuration
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceSetCacheConfig,
 * ::cudaDeviceGetCacheConfig,
 * ::cudaDeviceSetSharedMemConfig,
 * ::cudaFuncSetCacheConfig,
 * ::cuCtxGetSharedMemConfig
 */
extern __CUDA_DEPRECATED __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetSharedMemConfig(enum cudaSharedMemConfig *pConfig);

/**
 * \brief Sets the shared memory configuration for the current device.
 *
 * \deprecated
 *
 * On devices with configurable shared memory banks, this function will set
 * the shared memory bank size which is used for all subsequent kernel launches.
 * Any per-function setting of shared memory set via ::cudaFuncSetSharedMemConfig
 * will override the device wide setting.
 *
 * Changing the shared memory configuration between launches may introduce
 * a device side synchronization point.
 *
 * Changing the shared memory bank size will not increase shared memory usage
 * or affect occupancy of kernels, but may have major effects on performance. 
 * Larger bank sizes will allow for greater potential bandwidth to shared memory,
 * but will change what kinds of accesses to shared memory will result in bank 
 * conflicts.
 *
 * This function will do nothing on devices with fixed shared memory bank size.
 *
 * The supported bank configurations are:
 * - ::cudaSharedMemBankSizeDefault: set bank width the device default (currently,
 *   four bytes)
 * - ::cudaSharedMemBankSizeFourByte: set shared memory bank width to be four bytes
 *   natively.
 * - ::cudaSharedMemBankSizeEightByte: set shared memory bank width to be eight 
 *   bytes natively.
 *
 * \param config - Requested cache configuration
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceSetCacheConfig,
 * ::cudaDeviceGetCacheConfig,
 * ::cudaDeviceGetSharedMemConfig,
 * ::cudaFuncSetCacheConfig,
 * ::cuCtxSetSharedMemConfig
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaDeviceSetSharedMemConfig(enum cudaSharedMemConfig config);
/** @} */ /* END CUDART_DEVICE_DEPRECATED */


/**
 * \defgroup CUDART_ERROR Error Handling
 *
 * ___MANBRIEF___ error handling functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the error handling functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Returns the last error from a runtime call
 *
 * Returns the last error that has been produced by any of the runtime calls
 * in the same instance of the CUDA Runtime library in the host thread and
 * resets it to ::cudaSuccess.
 *
 * Note: Multiple instances of the CUDA Runtime library can be present in an
 * application when using a library that statically links the CUDA Runtime.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorMissingConfiguration,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorInitializationError,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorLaunchTimeout,
 * ::cudaErrorLaunchOutOfResources,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidConfiguration,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorUnmapBufferObjectFailed,
 * ::cudaErrorInvalidDevicePointer,
 * ::cudaErrorInvalidTexture,
 * ::cudaErrorInvalidTextureBinding,
 * ::cudaErrorInvalidChannelDescriptor,
 * ::cudaErrorInvalidMemcpyDirection,
 * ::cudaErrorInvalidFilterSetting,
 * ::cudaErrorInvalidNormSetting,
 * ::cudaErrorUnknown,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorInsufficientDriver,
 * ::cudaErrorNoDevice,
 * ::cudaErrorSetOnActiveProcess,
 * ::cudaErrorStartupFailure,
 * ::cudaErrorInvalidPtx,
 * ::cudaErrorUnsupportedPtxVersion,
 * ::cudaErrorNoKernelImageForDevice,
 * ::cudaErrorJitCompilerNotFound,
 * ::cudaErrorJitCompilationDisabled
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaPeekAtLastError, ::cudaGetErrorName, ::cudaGetErrorString, ::cudaError
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetLastError(void);

/**
 * \brief Returns the last error from a runtime call
 *
 * Returns the last error that has been produced by any of the runtime calls
 * in the same instance of the CUDA Runtime library in the host thread. This
 * call does not reset the error to ::cudaSuccess like ::cudaGetLastError().
 *
 * Note: Multiple instances of the CUDA Runtime library can be present in an
 * application when using a library that statically links the CUDA Runtime.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorMissingConfiguration,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorInitializationError,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorLaunchTimeout,
 * ::cudaErrorLaunchOutOfResources,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidConfiguration,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorUnmapBufferObjectFailed,
 * ::cudaErrorInvalidDevicePointer,
 * ::cudaErrorInvalidTexture,
 * ::cudaErrorInvalidTextureBinding,
 * ::cudaErrorInvalidChannelDescriptor,
 * ::cudaErrorInvalidMemcpyDirection,
 * ::cudaErrorInvalidFilterSetting,
 * ::cudaErrorInvalidNormSetting,
 * ::cudaErrorUnknown,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorInsufficientDriver,
 * ::cudaErrorNoDevice,
 * ::cudaErrorSetOnActiveProcess,
 * ::cudaErrorStartupFailure,
 * ::cudaErrorInvalidPtx,
 * ::cudaErrorUnsupportedPtxVersion,
 * ::cudaErrorNoKernelImageForDevice,
 * ::cudaErrorJitCompilerNotFound,
 * ::cudaErrorJitCompilationDisabled
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetLastError, ::cudaGetErrorName, ::cudaGetErrorString, ::cudaError
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaPeekAtLastError(void);

/**
 * \brief Returns the string representation of an error code enum name
 *
 * Returns a string containing the name of an error code in the enum.  If the error
 * code is not recognized, "unrecognized error code" is returned.
 *
 * \param error - Error code to convert to string
 *
 * \return
 * \p char* pointer to a NULL-terminated string
 *
 * \sa ::cudaGetErrorString, ::cudaGetLastError, ::cudaPeekAtLastError, ::cudaError,
 * ::cuGetErrorName
 */
extern __host__ __cudart_builtin__ const char* CUDARTAPI cudaGetErrorName(cudaError_t error);

/**
 * \brief Returns the description string for an error code
 *
 * Returns the description string for an error code.  If the error
 * code is not recognized, "unrecognized error code" is returned.
 *
 * \param error - Error code to convert to string
 *
 * \return
 * \p char* pointer to a NULL-terminated string
 *
 * \sa ::cudaGetErrorName, ::cudaGetLastError, ::cudaPeekAtLastError, ::cudaError,
 * ::cuGetErrorString
 */
extern __host__ __cudart_builtin__ const char* CUDARTAPI cudaGetErrorString(cudaError_t error);
/** @} */ /* END CUDART_ERROR */

/**
 * \addtogroup CUDART_DEVICE 
 *
 * @{
 */

/**
 * \brief Returns the number of compute-capable devices
 *
 * Returns in \p *count the number of devices with compute capability greater
 * or equal to 2.0 that are available for execution.
 *
 * \param count - Returns the number of devices with compute capability
 * greater or equal to 2.0
 *
 * \return
 * ::cudaSuccess
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDevice, ::cudaSetDevice, ::cudaGetDeviceProperties,
 * ::cudaChooseDevice, 
 * ::cudaInitDevice,
 * ::cuDeviceGetCount
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDeviceCount(int *count);

/**
 * \brief Returns information about the compute-device
 *
 * Returns in \p *prop the properties of device \p dev.
 * \param prop   - Properties for the specified device
 * \param device - Device number to get properties for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice, ::cudaChooseDevice,
 * ::cudaDeviceGetAttribute, 
 * ::cudaInitDevice,
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetName
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDeviceProperties(struct cudaDeviceProp *prop, int device);

/**
 * \brief Returns information about the device
 *
 * Returns in \p *value the integer value of the attribute \p attr on device
 * \p device.
 *
 * \param value  - Returned device attribute value
 * \param attr   - Device attribute to query
 * \param device - Device number to query
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice, ::cudaChooseDevice,
 * ::cudaGetDeviceProperties,
 * ::cudaInitDevice,
 * ::cuDeviceGetAttribute
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetAttribute(int *value, enum cudaDeviceAttr attr, int device);

/**
 * \brief Queries details about atomic operations supported between the device and host.
 *
 * Returns in \p *capabilities the details about requested atomic \p *operations over the 
 * the link between \p dev and the host. The allocated size of \p *operations and 
 * \p *capabilities must be \p count.
 *
 * For each ::cudaAtomicOperation in \p *operations, the corresponding result in \p *capabilities
 * will be a bitmask indicating which of ::cudaAtomicOperationCapability the link supports natively.
 *
 * Returns ::cudaErrorInvalidDevice if \p dev is not valid.
 *
 * Returns ::cudaErrorInvalidValue if \p *capabilities or \p *operations is NULL, if \p count is 0,
 * or if any of \p *operations is not valid.
 *
 * \param capabilities          - Returned capability details of each requested operation
 * \param operations            - Requested operations
 * \param count                 - Count of requested operations and size of capabilities
 * \param dev                   - Device handle
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue
 * \notefnerr
 *
 * \sa
 * ::cudaDeviceGetAttribute,
 * ::cudaDeviceGetP2PAtomicCapabilities,
 * ::cuDeviceGeHostAtomicCapabilities
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetHostAtomicCapabilities(unsigned int *capabilities, const enum cudaAtomicOperation* operations, unsigned int count, int device);

/**
 * \brief Returns the default mempool of a device
 *
 * The default mempool of a device contains device memory from that device.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue
 * ::cudaErrorNotSupported
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cuDeviceGetDefaultMemPool, ::cudaMallocAsync, ::cudaMemPoolTrimTo, ::cudaMemPoolGetAttribute, ::cudaDeviceSetMemPool, ::cudaMemPoolSetAttribute, ::cudaMemPoolSetAccess
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetDefaultMemPool(cudaMemPool_t *memPool, int device);


/**
 * \brief Sets the current memory pool of a device
 *
 * The memory pool must be local to the specified device.
 * Unless a mempool is specified in the ::cudaMallocAsync call,
 * ::cudaMallocAsync allocates from the current mempool of the provided stream's device.
 * By default, a device's current memory pool is its default memory pool.
 *
 * \note Use ::cudaMallocFromPoolAsync to specify asynchronous allocations from a device different
 * than the one the stream runs on.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorInvalidDevice
 * ::cudaErrorNotSupported
 * \notefnerr
 * \note_callback
 *
 * \sa ::cuDeviceSetMemPool, ::cudaDeviceGetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaMemPoolCreate, ::cudaMemPoolDestroy, ::cudaMallocFromPoolAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceSetMemPool(int device, cudaMemPool_t memPool);

/**
 * \brief Gets the current mempool for a device
 *
 * Returns the last pool provided to ::cudaDeviceSetMemPool for this device
 * or the device's default memory pool if ::cudaDeviceSetMemPool has never been called.
 * By default the current mempool is the default mempool for a device,
 * otherwise the returned pool must have been set with ::cuDeviceSetMemPool or ::cudaDeviceSetMemPool.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorNotSupported
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cuDeviceGetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceSetMemPool
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetMemPool(cudaMemPool_t *memPool, int device);

/**
 * \brief Return NvSciSync attributes that this device can support.
 *
 * Returns in \p nvSciSyncAttrList, the properties of NvSciSync that
 * this CUDA device, \p dev can support. The returned \p nvSciSyncAttrList
 * can be used to create an NvSciSync that matches this device's capabilities.
 * 
 * If NvSciSyncAttrKey_RequiredPerm field in \p nvSciSyncAttrList is
 * already set this API will return ::cudaErrorInvalidValue.
 * 
 * The applications should set \p nvSciSyncAttrList to a valid 
 * NvSciSyncAttrList failing which this API will return
 * ::cudaErrorInvalidHandle.
 * 
 * The \p flags controls how applications intends to use
 * the NvSciSync created from the \p nvSciSyncAttrList. The valid flags are:
 * - ::cudaNvSciSyncAttrSignal, specifies that the applications intends to 
 * signal an NvSciSync on this CUDA device.
 * - ::cudaNvSciSyncAttrWait, specifies that the applications intends to 
 * wait on an NvSciSync on this CUDA device.
 *
 * At least one of these flags must be set, failing which the API
 * returns ::cudaErrorInvalidValue. Both the flags are orthogonal
 * to one another: a developer may set both these flags that allows to
 * set both wait and signal specific attributes in the same \p nvSciSyncAttrList.
 *
 * Note that this API updates the input \p nvSciSyncAttrList with values equivalent
 * to the following public attribute key-values:
 * NvSciSyncAttrKey_RequiredPerm is set to
 * - NvSciSyncAccessPerm_SignalOnly if ::cudaNvSciSyncAttrSignal is set in \p flags.
 * - NvSciSyncAccessPerm_WaitOnly if ::cudaNvSciSyncAttrWait is set in \p flags.
 * - NvSciSyncAccessPerm_WaitSignal if both ::cudaNvSciSyncAttrWait and
 * ::cudaNvSciSyncAttrSignal are set in \p flags.
 * NvSciSyncAttrKey_PrimitiveInfo is set to
 * - NvSciSyncAttrValPrimitiveType_SysmemSemaphore on any valid \p device.
 * - NvSciSyncAttrValPrimitiveType_Syncpoint if \p device is a Tegra device.
 * - NvSciSyncAttrValPrimitiveType_SysmemSemaphorePayload64b if \p device is GA10X+.
 * NvSciSyncAttrKey_GpuId is set to the same UUID that is returned in 
 * \p cudaDeviceProp.uuid from ::cudaDeviceGetProperties for this \p device.
 *
 * \param nvSciSyncAttrList     - Return NvSciSync attributes supported.
 * \param device                - Valid Cuda Device to get NvSciSync attributes for.
 * \param flags                 - flags describing NvSciSync usage.
 *
 * \return
 *
 * ::cudaSuccess,
 * ::cudaErrorDeviceUninitialized,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidHandle,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorNotSupported,
 * ::cudaErrorMemoryAllocation
 *
 * \sa
 * ::cudaImportExternalSemaphore,
 * ::cudaDestroyExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetNvSciSyncAttributes(void *nvSciSyncAttrList, int device, int flags);

/**
 * \brief Queries attributes of the link between two devices.
 *
 * Returns in \p *value the value of the requested attribute \p attrib of the
 * link between \p srcDevice and \p dstDevice. The supported attributes are:
 * - ::cudaDevP2PAttrPerformanceRank: A relative value indicating the
 *   performance of the link between two devices. Lower value means better
 *   performance (0 being the value used for most performant link).
 * - ::cudaDevP2PAttrAccessSupported: 1 if peer access is enabled.
 * - ::cudaDevP2PAttrNativeAtomicSupported: 1 if all native atomic operations 
 *   over the link are supported.
 * - ::cudaDevP2PAttrCudaArrayAccessSupported: 1 if accessing CUDA arrays over
 *   the link is supported.
 * - ::cudaDevP2PAttrOnlyPartialNativeAtomicSupported: 1 if some 
 *   CUDA-valid atomic operations over the link are supported. Information about
 *   specific operations can be retrieved with ::cudaDeviceGetP2PAtomicCapabilities.
 *
 * Returns ::cudaErrorInvalidDevice if \p srcDevice or \p dstDevice are not valid
 * or if they represent the same device.
 *
 * Returns ::cudaErrorInvalidValue if \p attrib is not valid or if \p value is
 * a null pointer.
 *
 * \param value         - Returned value of the requested attribute
 * \param attrib        - The requested attribute of the link between \p srcDevice and \p dstDevice.
 * \param srcDevice     - The source device of the target link.
 * \param dstDevice     - The destination device of the target link.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceEnablePeerAccess,
 * ::cudaDeviceDisablePeerAccess,
 * ::cudaDeviceCanAccessPeer,
 * ::cuDeviceGetP2PAttribute
 * ::cudaDeviceGetP2PAtomicCapabilities
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetP2PAttribute(int *value, enum cudaDeviceP2PAttr attr, int srcDevice, int dstDevice);


/**
 * \brief Queries details about atomic operations supported between two devices
 *
 * Returns in \p *capabilities the details about requested atomic \p *operations over the 
 * the link between \p srcDevice and \p dstDevice. The allocated size of \p *operations and 
 * \p *capabilities must be \p count.
 *
 * For each ::cudaAtomicOperation in \p *operations, the corresponding result in \p *capabilities
 * will be a bitmask indicating which of ::cudaAtomicOperationCapability the link supports natively.
 *
 * Returns ::cudaErrorInvalidDevice if \p srcDevice or \p dstDevice are not valid
 * or if they represent the same device.
 *
 * Returns ::cudaErrorInvalidValue if \p *capabilities or \p *operations is NULL, if \p count is 0,
 * or if any of \p *operations is not valid.
 *
 * \param capabilities          - Returned capability details of each requested operation
 * \param operations            - Requested operations
 * \param count                 - Count of requested operations and size of capabilities
 * \param srcDevice             - The source device of the target link
 * \param dstDevice             - The destination device of the target link
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue
 * \notefnerr
 *
 * \sa
 * ::cudaDeviceGetP2PAttribute,
 * ::cuDeviceGetP2PAttribute,
 * ::cuDeviceGetP2PAtomicCapabilities
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetP2PAtomicCapabilities(unsigned int *capabilities, const enum cudaAtomicOperation *operations, unsigned int count, int srcDevice, int dstDevice);


/**
 * \brief Select compute-device which best matches criteria
 *
 * Returns in \p *device the device which has properties that best match
 * \p *prop.
 *
 * \param device - Device with best match
 * \param prop   - Desired device properties
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice,
 * ::cudaGetDeviceProperties, 
 * ::cudaInitDevice
 */
extern __host__ cudaError_t CUDARTAPI cudaChooseDevice(int *device, const struct cudaDeviceProp *prop);
/**
 * \brief Initialize device to be used for GPU executions
 *
 * This function will initialize the CUDA Runtime structures and primary context on \p device when called,
 * but the context will not be made current to \p device.
 *
 * When ::cudaInitDeviceFlagsAreValid is set in \p flags, deviceFlags are applied to the requested device.
 * The values of deviceFlags match those of the flags parameters in ::cudaSetDeviceFlags. 
 * The effect may be verified by ::cudaGetDeviceFlags.
 *
 * This function will return an error if the device is in ::cudaComputeModeExclusiveProcess
 * and is occupied by another process or if the device is in ::cudaComputeModeProhibited.
 *
 * \param device - Device on which the runtime will initialize itself.
 * \param deviceFlags - Parameters for device operation.
 * \param flags - Flags for controlling the device initialization.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaGetDeviceProperties,
 * ::cudaChooseDevice, ::cudaSetDevice
 * ::cuCtxSetCurrent
 */
extern __host__ cudaError_t CUDARTAPI cudaInitDevice(int device, unsigned int deviceFlags, unsigned int flags);
/**
 * \brief Set device to be used for GPU executions
 *
 * Sets \p device as the current device for the calling host thread.
 * Valid device id's are 0 to (::cudaGetDeviceCount() - 1).
 *
 * Any device memory subsequently allocated from this host thread
 * using ::cudaMalloc(), ::cudaMallocPitch() or ::cudaMallocArray()
 * will be physically resident on \p device.  Any host memory allocated
 * from this host thread using ::cudaMallocHost() or ::cudaHostAlloc() 
 * or ::cudaHostRegister() will have its lifetime associated  with
 * \p device.  Any streams or events created from this host thread will 
 * be associated with \p device.  Any kernels launched from this host
 * thread using the <<<>>> operator or ::cudaLaunchKernel() will be executed
 * on \p device.
 *
 * This call may be made from any host thread, to any device, and at 
 * any time.  This function will do no synchronization with the previous 
 * or new device, 
 * and should only take significant time when it initializes the runtime's context state.
 * This call will bind the primary context of the specified device to the calling thread and all the
 * subsequent memory allocations, stream and event creations, and kernel launches
 * will be associated with the primary context. 
 * This function will also immediately initialize the runtime state on the primary context, 
 * and the context will be current on \p device immediately. This function will return an 
 * error if the device is in ::cudaComputeModeExclusiveProcess and is occupied by another 
 * process or if the device is in ::cudaComputeModeProhibited.
 * 
 * It is not required to call ::cudaInitDevice before using this function.
 * \param device - Device on which the active host thread should execute the
 * device code.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorDeviceUnavailable,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaGetDeviceProperties,
 * ::cudaChooseDevice,
 * ::cudaInitDevice,
 * ::cuCtxSetCurrent
 */
extern __host__ cudaError_t CUDARTAPI cudaSetDevice(int device);

/**
 * \brief Returns which device is currently being used
 *
 * Returns in \p *device the current device for the calling host thread.
 *
 * \param device - Returns the device on which the active host thread
 * executes the device code.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorDeviceUnavailable,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaSetDevice, ::cudaGetDeviceProperties,
 * ::cudaChooseDevice,
 * ::cuCtxGetCurrent
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDevice(int *device);

/**
 * \brief Set a list of devices that can be used for CUDA
 *
 * Sets a list of devices for CUDA execution in priority order using
 * \p device_arr. The parameter \p len specifies the number of elements in the
 * list.  CUDA will try devices from the list sequentially until it finds one
 * that works.  If this function is not called, or if it is called with a \p len
 * of 0, then CUDA will go back to its default behavior of trying devices
 * sequentially from a default list containing all of the available CUDA
 * devices in the system. If a specified device ID in the list does not exist,
 * this function will return ::cudaErrorInvalidDevice. If \p len is not 0 and
 * \p device_arr is NULL or if \p len exceeds the number of devices in
 * the system, then ::cudaErrorInvalidValue is returned.
 *
 * \param device_arr - List of devices to try
 * \param len        - Number of devices in specified list
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaSetDevice, ::cudaGetDeviceProperties,
 * ::cudaSetDeviceFlags,
 * ::cudaChooseDevice
 */
extern __host__ cudaError_t CUDARTAPI cudaSetValidDevices(int *device_arr, int len);

/**
 * \brief Sets flags to be used for device executions
 * 
 * Records \p flags as the flags for the current device. If the current device
 * has been set and that device has already been initialized, the previous flags
 * are overwritten. If the current device has not been initialized, it is
 * initialized with the provided flags. If no device has been made current to
 * the calling thread, a default device is selected and initialized with the
 * provided flags.
 * 
 * The three LSBs of the \p flags parameter can be used to control how the CPU
 * thread interacts with the OS scheduler when waiting for results from the
 * device.
 *
 * - ::cudaDeviceScheduleAuto: The default value if the \p flags parameter is
 * zero, uses a heuristic based on the number of active CUDA contexts in the
 * process \p C and the number of logical processors in the system \p P. If
 * \p C \> \p P, then CUDA will yield to other OS threads when waiting for the
 * device, otherwise CUDA will not yield while waiting for results and
 * actively spin on the processor. Additionally, on Tegra devices,
 * ::cudaDeviceScheduleAuto uses a heuristic based on the power profile of
 * the platform and may choose ::cudaDeviceScheduleBlockingSync for low-powered
 * devices.
 * - ::cudaDeviceScheduleSpin: Instruct CUDA to actively spin when waiting for
 * results from the device. This can decrease latency when waiting for the
 * device, but may lower the performance of CPU threads if they are performing
 * work in parallel with the CUDA thread.
 * - ::cudaDeviceScheduleYield: Instruct CUDA to yield its thread when waiting
 * for results from the device. This can increase latency when waiting for the
 * device, but can increase the performance of CPU threads performing work in
 * parallel with the device.
 * - ::cudaDeviceScheduleBlockingSync: Instruct CUDA to block the CPU thread 
 * on a synchronization primitive when waiting for the device to finish work.
 * - ::cudaDeviceBlockingSync: Instruct CUDA to block the CPU thread on a 
 * synchronization primitive when waiting for the device to finish work. <br>
 * \ref deprecated "Deprecated:" This flag was deprecated as of CUDA 4.0 and
 * replaced with ::cudaDeviceScheduleBlockingSync.
 * - ::cudaDeviceMapHost: This flag enables allocating pinned
 * host memory that is accessible to the device. It is implicit for the
 * runtime but may be absent if a context is created using the driver API.
 * If this flag is not set, ::cudaHostGetDevicePointer() will always return
 * a failure code.
 * - ::cudaDeviceLmemResizeToMax: Instruct CUDA to not reduce local memory
 * after resizing local memory for a kernel. This can prevent thrashing by
 * local memory allocations when launching many kernels with high local
 * memory usage at the cost of potentially increased memory usage. <br>
 * \ref deprecated "Deprecated:" This flag is deprecated and the behavior enabled
 * by this flag is now the default and cannot be disabled.
 * - ::cudaDeviceSyncMemops: Ensures that synchronous memory operations initiated
 * on this context will always synchronize. See further documentation in the
 * section titled "API Synchronization behavior" to learn more about cases when
 * synchronous memory operations can exhibit asynchronous behavior.
 *
 * \param flags - Parameters for device operation
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceFlags, ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaGetDeviceProperties,
 * ::cudaSetDevice, ::cudaSetValidDevices,
 * ::cudaInitDevice,
 * ::cudaChooseDevice,
 * ::cuDevicePrimaryCtxSetFlags
 */
extern __host__ cudaError_t CUDARTAPI cudaSetDeviceFlags( unsigned int flags );

/**
 * \brief Gets the flags for the current device
 *
 * 
 * Returns in \p flags the flags for the current device. If there is a current
 * device for the calling thread, the flags for the device are returned. If
 * there is no current device, the flags for the first device are returned,
 * which may be the default flags.  Compare to the behavior of
 * ::cudaSetDeviceFlags.
 *
 * Typically, the flags returned should match the behavior that will be seen
 * if the calling thread uses a device after this call, without any change to
 * the flags or current device inbetween by this or another thread.  Note that
 * if the device is not initialized, it is possible for another thread to
 * change the flags for the current device before it is initialized.
 * Additionally, when using exclusive mode, if this thread has not requested a
 * specific device, it may use a device other than the first device, contrary
 * to the assumption made by this function.
 *
 * If a context has been created via the driver API and is current to the
 * calling thread, the flags for that context are always returned.
 *
 * Flags returned by this function may specifically include ::cudaDeviceMapHost
 * even though it is not accepted by ::cudaSetDeviceFlags because it is
 * implicit in runtime API flags.  The reason for this is that the current
 * context may have been created via the driver API in which case the flag is
 * not implicit and may be unset.
 *
 * \param flags - Pointer to store the device flags
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDevice, ::cudaGetDeviceProperties,
 * ::cudaSetDevice, ::cudaSetDeviceFlags,
 * ::cudaInitDevice,
 * ::cuCtxGetFlags,
 * ::cuDevicePrimaryCtxGetState
 */
extern __host__ cudaError_t CUDARTAPI cudaGetDeviceFlags( unsigned int *flags );
/** @} */ /* END CUDART_DEVICE */

/**
 * \defgroup CUDART_STREAM Stream Management
 *
 * ___MANBRIEF___ stream management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the stream management functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Create an asynchronous stream
 *
 * Creates a new asynchronous stream on the context that is current to the calling host thread.
 * If no context is current to the calling host thread, then the primary context for a device
 * is selected, made current to the calling thread, and initialized before creating a stream on it.
 *
 * \param pStream - Pointer to new stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreateWithPriority,
 * ::cudaStreamCreateWithFlags,
 * ::cudaStreamGetPriority,
 * ::cudaStreamGetFlags,
 * ::cudaStreamGetDevice,
 * ::cudaStreamGetDevResource,
 * ::cudaStreamQuery,
 * ::cudaStreamSynchronize,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamAddCallback,
 * ::cudaSetDevice,
 * ::cudaStreamDestroy,
 * ::cuStreamCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamCreate(cudaStream_t *pStream);

/**
 * \brief Create an asynchronous stream
 *
 * Creates a new asynchronous stream on the context that is current to the calling host thread.
 * If no context is current to the calling host thread, then the primary context for a device
 * is selected, made current to the calling thread, and initialized before creating a stream on it.
 * The \p flags argument determines the behaviors of the stream.  Valid values for \p flags are
 * - ::cudaStreamDefault: Default stream creation flag.
 * - ::cudaStreamNonBlocking: Specifies that work running in the created 
 *   stream may run concurrently with work in stream 0 (the NULL stream), and that
 *   the created stream should perform no implicit synchronization with stream 0.
 *
 * \param pStream - Pointer to new stream identifier
 * \param flags   - Parameters for stream creation
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate,
 * ::cudaStreamCreateWithPriority,
 * ::cudaStreamGetFlags,
 * ::cudaStreamGetDevice,
 * ::cudaStreamGetDevResource,
 * ::cudaStreamQuery,
 * ::cudaStreamSynchronize,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamAddCallback,
 * ::cudaSetDevice,
 * ::cudaStreamDestroy,
 * ::cuStreamCreate
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamCreateWithFlags(cudaStream_t *pStream, unsigned int flags);

/**
 * \brief Create an asynchronous stream with the specified priority
 *
 * Creates a stream with the specified priority and returns a handle in \p pStream.
 * The stream is created on the context that is current to the calling host thread.
 * If no context is current to the calling host thread, then the primary context for a device
 * is selected, made current to the calling thread, and initialized before creating a stream on it.
 * This affects the scheduling priority of work in the stream. Priorities provide a
 * hint to preferentially run work with higher priority when possible, but do
 * not preempt already-running work or provide any other functional guarantee on
 * execution order.
 *
 * \p priority follows a convention where lower numbers represent higher priorities.
 * '0' represents default priority. The range of meaningful numerical priorities can
 * be queried using ::cudaDeviceGetStreamPriorityRange. If the specified priority is
 * outside the numerical range returned by ::cudaDeviceGetStreamPriorityRange,
 * it will automatically be clamped to the lowest or the highest number in the range.
 *
 * \param pStream  - Pointer to new stream identifier
 * \param flags    - Flags for stream creation. See ::cudaStreamCreateWithFlags for a list of valid flags that can be passed
 * \param priority - Priority of the stream. Lower numbers represent higher priorities.
 *                   See ::cudaDeviceGetStreamPriorityRange for more information about
 *                   the meaningful stream priorities that can be passed.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \note Stream priorities are supported only on GPUs
 * with compute capability 3.5 or higher.
 *
 * \note In the current implementation, only compute kernels launched in
 * priority streams are affected by the stream's priority. Stream priorities have
 * no effect on host-to-device and device-to-host memory operations.
 *
 * \sa ::cudaStreamCreate,
 * ::cudaStreamCreateWithFlags,
 * ::cudaDeviceGetStreamPriorityRange,
 * ::cudaStreamGetPriority,
 * ::cudaStreamQuery,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamAddCallback,
 * ::cudaStreamSynchronize,
 * ::cudaSetDevice,
 * ::cudaStreamDestroy,
 * ::cuStreamCreateWithPriority
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamCreateWithPriority(cudaStream_t *pStream, unsigned int flags, int priority);

/**
 * \brief Query the priority of a stream
 *
 * Query the priority of a stream. The priority is returned in in \p priority.
 * Note that if the stream was created with a priority outside the meaningful
 * numerical range returned by ::cudaDeviceGetStreamPriorityRange,
 * this function returns the clamped priority.
 * See ::cudaStreamCreateWithPriority for details about priority clamping.
 *
 * \param hStream    - Handle to the stream to be queried
 * \param priority   - Pointer to a signed integer in which the stream's priority is returned
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreateWithPriority,
 * ::cudaDeviceGetStreamPriorityRange,
 * ::cudaStreamGetFlags,
 * ::cudaStreamGetDevice,
 * ::cudaStreamGetDevResource,
 * ::cuStreamGetPriority
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetPriority(cudaStream_t hStream, int *priority);

/**
 * \brief Query the flags of a stream
 *
 * Query the flags of a stream. The flags are returned in \p flags.
 * See ::cudaStreamCreateWithFlags for a list of valid flags.
 *
 * \param hStream - Handle to the stream to be queried
 * \param flags   - Pointer to an unsigned integer in which the stream's flags are returned
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreateWithPriority,
 * ::cudaStreamCreateWithFlags,
 * ::cudaStreamGetPriority,
 * ::cudaStreamGetDevice,
 * ::cuStreamGetFlags
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetFlags(cudaStream_t hStream, unsigned int *flags);

/**
 * \brief Query the Id of a stream
 *
 * Query the Id of a stream. The Id is returned in \p streamId.
 * The Id is unique for the life of the program.
 *
 * The stream handle \p hStream can refer to any of the following:
 * <ul>
 *   <li>a stream created via any of the CUDA runtime APIs such as ::cudaStreamCreate, 
 *   ::cudaStreamCreateWithFlags and ::cudaStreamCreateWithPriority, or their driver 
 *   API equivalents such as ::cuStreamCreate or ::cuStreamCreateWithPriority.
 *   Passing an invalid handle will result in undefined behavior.</li>
 *   <li>any of the special streams such as the NULL stream, ::cudaStreamLegacy 
 *   and ::cudaStreamPerThread respectively.  The driver API equivalents of these 
 *   are also accepted which are NULL, ::CU_STREAM_LEGACY and ::CU_STREAM_PER_THREAD.</li>
 * </ul>
 * 
 * \param hStream    - Handle to the stream to be queried
 * \param streamId   - Pointer to an unsigned long long in which the stream Id is returned
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreateWithPriority,
 * ::cudaStreamCreateWithFlags,
 * ::cudaStreamGetPriority,
 * ::cudaStreamGetFlags,
 * ::cuStreamGetId
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetId(cudaStream_t hStream, unsigned long long *streamId);

/**
 * \brief Query the device of a stream
 *
 * Returns in \p *device the device of the stream.
 *
 * \param hStream - Handle to the stream to be queried
 * \param device - Returns the device to which the stream belongs
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorDeviceUnavailable,
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaSetDevice,
 * ::cudaGetDevice,
 * ::cudaStreamCreate,
 * ::cudaStreamGetPriority,
 * ::cudaStreamGetFlags,
 * ::cuStreamGetId
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetDevice(cudaStream_t hStream, int *device);

/**
 * \brief Resets all persisting lines in cache to normal status.
 *
 * Resets all persisting lines in cache to normal status.
 * Takes effect on function return.
 *
 * \return
 * ::cudaSuccess,
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ cudaError_t CUDARTAPI cudaCtxResetPersistingL2Cache(void);

/**
 * \brief Copies attributes from source stream to destination stream.
 *
 * Copies attributes from source stream \p src to destination stream \p dst.
 * Both streams must have the same context.
 *
 * \param[out] dst Destination stream
 * \param[in] src Source stream
 * For attributes see ::cudaStreamAttrID
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotSupported
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamCopyAttributes(cudaStream_t dst, cudaStream_t src);

 /**
 * \brief Queries stream attribute.
 *
 * Queries attribute \p attr from \p hStream and stores it in corresponding
 * member of \p value_out.
 *
 * \param[in] hStream
 * \param[in] attr
 * \param[out] value_out
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetAttribute(
        cudaStream_t hStream, cudaStreamAttrID attr,
        cudaStreamAttrValue *value_out);

 /**
 * \brief Sets stream attribute.
 *
 * Sets attribute \p attr on \p hStream from corresponding attribute of
 * \p value. The updated attribute will be applied to subsequent work
 * submitted to the stream. It will not affect previously submitted work.
 *
 * \param[out] hStream
 * \param[in] attr
 * \param[in] value
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamSetAttribute(
        cudaStream_t hStream, cudaStreamAttrID attr,
        const cudaStreamAttrValue *value);

 /**
 * \brief Destroys and cleans up an asynchronous stream
 *
 * Destroys and cleans up the asynchronous stream specified by \p stream.
 *
 * In case the device is still doing work in the stream \p stream
 * when ::cudaStreamDestroy() is called, the function will return immediately 
 * and the resources associated with \p stream will be released automatically 
 * once the device has completed all work in \p stream.
 *
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * ::cudaErrorExternalDevice
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa ::cudaStreamCreate,
 * ::cudaStreamCreateWithFlags,
 * ::cudaStreamQuery,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamSynchronize,
 * ::cudaStreamAddCallback,
 * ::cuStreamDestroy
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamDestroy(cudaStream_t stream);

/**
 * \brief Make a compute stream wait on an event
 *
 * Makes all future work submitted to \p stream wait for all work captured in
 * \p event.  See ::cudaEventRecord() for details on what is captured by an event.
 * The synchronization will be performed efficiently on the device when applicable.
 * \p event may be from a different device than \p stream.
 *
 * flags include:
 * - ::cudaEventWaitDefault: Default event creation flag.
 * - ::cudaEventWaitExternal: Event is captured in the graph as an external
 *   event node when performing stream capture.
 *
 * \param stream - Stream to wait
 * \param event  - Event to wait on
 * \param flags  - Parameters for the operation(See above)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamQuery, ::cudaStreamSynchronize, ::cudaStreamAddCallback, ::cudaStreamDestroy,
 * ::cuStreamWaitEvent
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamWaitEvent(cudaStream_t stream, cudaEvent_t event, unsigned int flags __dv(0));

/**
 * Type of stream callback functions.
 * \param stream The stream as passed to ::cudaStreamAddCallback, may be NULL.
 * \param status ::cudaSuccess or any persistent error on the stream.
 * \param userData User parameter provided at registration.
 */
typedef void (CUDART_CB *cudaStreamCallback_t)(cudaStream_t stream, cudaError_t status, void *userData);

/**
 * \brief Add a callback to a compute stream
 *
 * \note This function is slated for eventual deprecation and removal. If
 * you do not require the callback to execute in case of a device error,
 * consider using ::cudaLaunchHostFunc. Additionally, this function is not
 * supported with ::cudaStreamBeginCapture and ::cudaStreamEndCapture, unlike
 * ::cudaLaunchHostFunc.
 *
 * Adds a callback to be called on the host after all currently enqueued
 * items in the stream have completed.  For each 
 * cudaStreamAddCallback call, a callback will be executed exactly once.
 * The callback will block later work in the stream until it is finished.
 *
 * The callback may be passed ::cudaSuccess or an error code.  In the event
 * of a device error, all subsequently executed callbacks will receive an
 * appropriate ::cudaError_t.
 *
 * Callbacks must not make any CUDA API calls.  Attempting to use CUDA APIs
 * may result in ::cudaErrorNotPermitted.  Callbacks must not perform any
 * synchronization that may depend on outstanding device work or other callbacks
 * that are not mandated to run earlier.  Callbacks without a mandated order
 * (in independent streams) execute in undefined order and may be serialized.
 *
 * For the purposes of Unified Memory, callback execution makes a number of
 * guarantees:
 * <ul>
 *   <li>The callback stream is considered idle for the duration of the
 *   callback.  Thus, for example, a callback may always use memory attached
 *   to the callback stream.</li>
 *   <li>The start of execution of a callback has the same effect as
 *   synchronizing an event recorded in the same stream immediately prior to
 *   the callback.  It thus synchronizes streams which have been "joined"
 *   prior to the callback.</li>
 *   <li>Adding device work to any stream does not have the effect of making
 *   the stream active until all preceding callbacks have executed.  Thus, for
 *   example, a callback might use global attached memory even if work has
 *   been added to another stream, if it has been properly ordered with an
 *   event.</li>
 *   <li>Completion of a callback does not cause a stream to become
 *   active except as described above.  The callback stream will remain idle
 *   if no device work follows the callback, and will remain idle across
 *   consecutive callbacks without device work in between.  Thus, for example,
 *   stream synchronization can be done by signaling from a callback at the
 *   end of the stream.</li>
 * </ul>
 *
 * \param stream   - Stream to add callback to
 * \param callback - The function to call once preceding stream operations are complete
 * \param userData - User specified data to be passed to the callback function
 * \param flags    - Reserved for future use, must be 0
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamQuery, ::cudaStreamSynchronize, ::cudaStreamWaitEvent, ::cudaStreamDestroy, ::cudaMallocManaged, ::cudaStreamAttachMemAsync,
 * ::cudaLaunchHostFunc, ::cuStreamAddCallback
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamAddCallback(cudaStream_t stream,
        cudaStreamCallback_t callback, void *userData, unsigned int flags);

/**
 * \brief Waits for stream tasks to complete
 *
 * Blocks until \p stream has completed all operations. If the
 * ::cudaDeviceScheduleBlockingSync flag was set for this device, 
 * the host thread will block until the stream is finished with 
 * all of its tasks.
 *
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamQuery, ::cudaStreamWaitEvent, ::cudaStreamAddCallback, ::cudaStreamDestroy,
 * ::cuStreamSynchronize
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamSynchronize(cudaStream_t stream);

/**
 * \brief Queries an asynchronous stream for completion status
 *
 * Returns ::cudaSuccess if all operations in \p stream have
 * completed, or ::cudaErrorNotReady if not.
 *
 * For the purposes of Unified Memory, a return value of ::cudaSuccess
 * is equivalent to having called ::cudaStreamSynchronize().
 *
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotReady,
 * ::cudaErrorInvalidResourceHandle
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamWaitEvent, ::cudaStreamSynchronize, ::cudaStreamAddCallback, ::cudaStreamDestroy,
 * ::cuStreamQuery
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamQuery(cudaStream_t stream);

/**
 * \brief Attach memory to a stream asynchronously
 *
 * Enqueues an operation in \p stream to specify stream association of
 * \p length bytes of memory starting from \p devPtr. This function is a
 * stream-ordered operation, meaning that it is dependent on, and will
 * only take effect when, previous work in stream has completed. Any
 * previous association is automatically replaced.
 *
 * \p devPtr must point to an one of the following types of memories:
 * - managed memory declared using the __managed__ keyword or allocated with
 *   ::cudaMallocManaged.
 * - a valid host-accessible region of system-allocated pageable memory. This
 *   type of memory may only be specified if the device associated with the
 *   stream reports a non-zero value for the device attribute
 *   ::cudaDevAttrPageableMemoryAccess.
 *
 * For managed allocations, \p length must be either zero or the entire
 * allocation's size. Both indicate that the entire allocation's stream
 * association is being changed. Currently, it is not possible to change stream
 * association for a portion of a managed allocation.
 *
 * For pageable allocations, \p length must be non-zero.
 *
 * The stream association is specified using \p flags which must be
 * one of ::cudaMemAttachGlobal, ::cudaMemAttachHost or ::cudaMemAttachSingle.
 * The default value for \p flags is ::cudaMemAttachSingle
 * If the ::cudaMemAttachGlobal flag is specified, the memory can be accessed
 * by any stream on any device.
 * If the ::cudaMemAttachHost flag is specified, the program makes a guarantee
 * that it won't access the memory on the device from any stream on a device that
 * has a zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess.
 * If the ::cudaMemAttachSingle flag is specified and \p stream is associated with
 * a device that has a zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess,
 * the program makes a guarantee that it will only access the memory on the device
 * from \p stream. It is illegal to attach singly to the NULL stream, because the
 * NULL stream is a virtual global stream and not a specific stream. An error will
 * be returned in this case.
 *
 * When memory is associated with a single stream, the Unified Memory system will
 * allow CPU access to this memory region so long as all operations in \p stream
 * have completed, regardless of whether other streams are active. In effect,
 * this constrains exclusive ownership of the managed memory region by
 * an active GPU to per-stream activity instead of whole-GPU activity.
 *
 * Accessing memory on the device from streams that are not associated with
 * it will produce undefined results. No error checking is performed by the
 * Unified Memory system to ensure that kernels launched into other streams
 * do not access this region. 
 *
 * It is a program's responsibility to order calls to ::cudaStreamAttachMemAsync
 * via events, synchronization or other means to ensure legal access to memory
 * at all times. Data visibility and coherency will be changed appropriately
 * for all kernels which follow a stream-association change.
 *
 * If \p stream is destroyed while data is associated with it, the association is
 * removed and the association reverts to the default visibility of the allocation
 * as specified at ::cudaMallocManaged. For __managed__ variables, the default
 * association is always ::cudaMemAttachGlobal. Note that destroying a stream is an
 * asynchronous operation, and as a result, the change to default association won't
 * happen until all work in the stream has completed.
 *
 * \param stream  - Stream in which to enqueue the attach operation
 * \param devPtr  - Pointer to memory (must be a pointer to managed memory or
 *                  to a valid host-accessible region of system-allocated
 *                  memory)
 * \param length  - Length of memory (defaults to zero)
 * \param flags   - Must be one of ::cudaMemAttachGlobal, ::cudaMemAttachHost or ::cudaMemAttachSingle (defaults to ::cudaMemAttachSingle)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotReady,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamWaitEvent, ::cudaStreamSynchronize, ::cudaStreamAddCallback, ::cudaStreamDestroy, ::cudaMallocManaged,
 * ::cuStreamAttachMemAsync
 */
#if defined(__cplusplus)
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamAttachMemAsync(cudaStream_t stream, void *devPtr, size_t length __dv(0), unsigned int flags = cudaMemAttachSingle);
#else
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamAttachMemAsync(cudaStream_t stream, void *devPtr, size_t length __dv(0), unsigned int flags);
#endif

/**
 * \brief Begins graph capture on a stream
 *
 * Begin graph capture on \p stream. When a stream is in capture mode, all operations
 * pushed into the stream will not be executed, but will instead be captured into
 * a graph, which will be returned via ::cudaStreamEndCapture. Capture may not be initiated
 * if \p stream is ::cudaStreamLegacy. Capture must be ended on the same stream in which
 * it was initiated, and it may only be initiated if the stream is not already in capture
 * mode. The capture mode may be queried via ::cudaStreamIsCapturing. A unique id
 * representing the capture sequence may be queried via ::cudaStreamGetCaptureInfo.
 *
 * If \p mode is not ::cudaStreamCaptureModeRelaxed, ::cudaStreamEndCapture must be
 * called on this stream from the same thread.
 *
 * \note Kernels captured using this API must not use texture and surface references.
 *       Reading or writing through any texture or surface reference is undefined
 *       behavior. This restriction does not apply to texture and surface objects.
 *
 * \param stream - Stream in which to initiate capture
 * \param mode    - Controls the interaction of this capture sequence with other API
 *                  calls that are potentially unsafe. For more details see
 *                  ::cudaThreadExchangeStreamCaptureMode.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 *
 * \sa
 * ::cudaStreamCreate,
 * ::cudaStreamIsCapturing,
 * ::cudaStreamEndCapture,
 * ::cudaThreadExchangeStreamCaptureMode
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCapture(cudaStream_t stream, enum cudaStreamCaptureMode mode);

/**
 * \brief Begins graph capture on a stream to an existing graph
 *
 * Begin graph capture on \p stream. When a stream is in capture mode, all operations
 * pushed into the stream will not be executed, but will instead be captured into
 * \p graph, which will be returned via ::cudaStreamEndCapture.
 *
 * Capture may not be initiated if \p stream is ::cudaStreamLegacy. Capture must be ended on the
 * same stream in which it was initiated, and it may only be initiated if the stream is not
 * already in capture mode. The capture mode may be queried via ::cudaStreamIsCapturing. A unique id
 * representing the capture sequence may be queried via ::cudaStreamGetCaptureInfo.
 *
 * If \p mode is not ::cudaStreamCaptureModeRelaxed, ::cudaStreamEndCapture must be
 * called on this stream from the same thread.
 *
 * \note Kernels captured using this API must not use texture and surface references.
 *       Reading or writing through any texture or surface reference is undefined
 *       behavior. This restriction does not apply to texture and surface objects.
 *
 * \param stream          - Stream in which to initiate capture.
 * \param graph           - Graph to capture into.
 * \param dependencies    - Dependencies of the first node captured in the stream.  Can be NULL if numDependencies is 0.
 * \param dependencyData  - Optional array of data associated with each dependency.
 * \param numDependencies - Number of dependencies.
 * \param mode            - Controls the interaction of this capture sequence with other API
 *                          calls that are potentially unsafe. For more details see
 *                          ::cudaThreadExchangeStreamCaptureMode.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 *
 * \sa
 * ::cudaStreamCreate,
 * ::cudaStreamIsCapturing,
 * ::cudaStreamEndCapture,
 * ::cudaThreadExchangeStreamCaptureMode
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCaptureToGraph(cudaStream_t stream, cudaGraph_t graph, const cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, enum cudaStreamCaptureMode mode);

/**
 * \brief Swaps the stream capture interaction mode for a thread
 *
 * Sets the calling thread's stream capture interaction mode to the value contained
 * in \p *mode, and overwrites \p *mode with the previous mode for the thread. To
 * facilitate deterministic behavior across function or module boundaries, callers
 * are encouraged to use this API in a push-pop fashion: \code
     cudaStreamCaptureMode mode = desiredMode;
     cudaThreadExchangeStreamCaptureMode(&mode);
     ...
     cudaThreadExchangeStreamCaptureMode(&mode); // restore previous mode
 * \endcode
 *
 * During stream capture (see ::cudaStreamBeginCapture), some actions, such as a call
 * to ::cudaMalloc, may be unsafe. In the case of ::cudaMalloc, the operation is
 * not enqueued asynchronously to a stream, and is not observed by stream capture.
 * Therefore, if the sequence of operations captured via ::cudaStreamBeginCapture
 * depended on the allocation being replayed whenever the graph is launched, the
 * captured graph would be invalid.
 *
 * Therefore, stream capture places restrictions on API calls that can be made within
 * or concurrently to a ::cudaStreamBeginCapture-::cudaStreamEndCapture sequence. This
 * behavior can be controlled via this API and flags to ::cudaStreamBeginCapture.
 *
 * A thread's mode is one of the following:
 * - \p cudaStreamCaptureModeGlobal: This is the default mode. If the local thread has
 *   an ongoing capture sequence that was not initiated with
 *   \p cudaStreamCaptureModeRelaxed at \p cuStreamBeginCapture, or if any other thread
 *   has a concurrent capture sequence initiated with \p cudaStreamCaptureModeGlobal,
 *   this thread is prohibited from potentially unsafe API calls.
 * - \p cudaStreamCaptureModeThreadLocal: If the local thread has an ongoing capture
 *   sequence not initiated with \p cudaStreamCaptureModeRelaxed, it is prohibited
 *   from potentially unsafe API calls. Concurrent capture sequences in other threads
 *   are ignored.
 * - \p cudaStreamCaptureModeRelaxed: The local thread is not prohibited from potentially
 *   unsafe API calls. Note that the thread is still prohibited from API calls which
 *   necessarily conflict with stream capture, for example, attempting ::cudaEventQuery
 *   on an event that was last recorded inside a capture sequence.
 *
 * \param mode - Pointer to mode value to swap with the current mode
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 *
 * \sa
 * ::cudaStreamBeginCapture
 */
extern __host__ cudaError_t CUDARTAPI cudaThreadExchangeStreamCaptureMode(enum cudaStreamCaptureMode *mode);

/**
 * \brief Ends capture on a stream, returning the captured graph
 *
 * End capture on \p stream, returning the captured graph via \p pGraph.
 * Capture must have been initiated on \p stream via a call to ::cudaStreamBeginCapture.
 * If capture was invalidated, due to a violation of the rules of stream capture, then
 * a NULL graph will be returned.
 *
 * If the \p mode argument to ::cudaStreamBeginCapture was not
 * ::cudaStreamCaptureModeRelaxed, this call must be from the same thread as
 * ::cudaStreamBeginCapture.
 *
 * \param stream - Stream to query
 * \param pGraph - The captured graph
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorStreamCaptureWrongThread
 * \notefnerr
 *
 * \sa
 * ::cudaStreamCreate,
 * ::cudaStreamBeginCapture,
 * ::cudaStreamIsCapturing,
 * ::cudaGraphDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamEndCapture(cudaStream_t stream, cudaGraph_t *pGraph);

/**
 * \brief Returns a stream's capture status
 *
 * Return the capture status of \p stream via \p pCaptureStatus. After a successful
 * call, \p *pCaptureStatus will contain one of the following:
 * - ::cudaStreamCaptureStatusNone: The stream is not capturing.
 * - ::cudaStreamCaptureStatusActive: The stream is capturing.
 * - ::cudaStreamCaptureStatusInvalidated: The stream was capturing but an error
 *   has invalidated the capture sequence. The capture sequence must be terminated
 *   with ::cudaStreamEndCapture on the stream where it was initiated in order to
 *   continue using \p stream.
 *
 * Note that, if this is called on ::cudaStreamLegacy (the "null stream") while
 * a blocking stream on the same device is capturing, it will return
 * ::cudaErrorStreamCaptureImplicit and \p *pCaptureStatus is unspecified
 * after the call. The blocking stream capture is not invalidated.
 *
 * When a blocking stream is capturing, the legacy stream is in an
 * unusable state until the blocking stream capture is terminated. The legacy
 * stream is not supported for stream capture, but attempted use would have an
 * implicit dependency on the capturing stream(s).
 *
 * \param stream         - Stream to query
 * \param pCaptureStatus - Returns the stream's capture status
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorStreamCaptureImplicit
 * \notefnerr
 *
 * \sa
 * ::cudaStreamCreate,
 * ::cudaStreamBeginCapture,
 * ::cudaStreamEndCapture
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamIsCapturing(cudaStream_t stream, enum cudaStreamCaptureStatus *pCaptureStatus);


/**
 * \brief Query a stream's capture state
 *
 * Query stream state related to stream capture.
 *
 * If called on ::cudaStreamLegacy (the "null stream") while a stream not created 
 * with ::cudaStreamNonBlocking is capturing, returns ::cudaErrorStreamCaptureImplicit.
 *
 * Valid data (other than capture status) is returned only if both of the following are true:
 * - the call returns cudaSuccess
 * - the returned capture status is ::cudaStreamCaptureStatusActive
 *
 * If \p edgeData_out is non-NULL then \p dependencies_out must be as well. If
 * \p dependencies_out is non-NULL and \p edgeData_out is NULL, but there is non-zero edge
 * data for one or more of the current stream dependencies, the call will return
 * ::cudaErrorLossyQuery.
 *
 * \param stream - The stream to query
 * \param captureStatus_out - Location to return the capture status of the stream; required
 * \param id_out - Optional location to return an id for the capture sequence, which is
 *           unique over the lifetime of the process
 * \param graph_out - Optional location to return the graph being captured into. All
 *           operations other than destroy and node removal are permitted on the graph
 *           while the capture sequence is in progress. This API does not transfer
 *           ownership of the graph, which is transferred or destroyed at
 *           ::cudaStreamEndCapture. Note that the graph handle may be invalidated before
 *           end of capture for certain errors. Nodes that are or become
 *           unreachable from the original stream at ::cudaStreamEndCapture due to direct
 *           actions on the graph do not trigger ::cudaErrorStreamCaptureUnjoined.
 * \param dependencies_out - Optional location to store a pointer to an array of nodes.
 *           The next node to be captured in the stream will depend on this set of nodes,
 *           absent operations such as event wait which modify this set. The array pointer
 *           is valid until the next API call which operates on the stream or until the
 *           capture is terminated. The node handles may be copied out and are valid until
 *           they or the graph is destroyed. The driver-owned array may also be passed
 *           directly to APIs that operate on the graph (not the stream) without copying.
 * \param edgeData_out - Optional location to store a pointer to an array of graph edge
 *           data. This array parallels \c dependencies_out; the next node to be added
 *           has an edge to \c dependencies_out[i] with annotation \c edgeData_out[i] for
 *           each \c i. The array pointer is valid until the next API call which operates
 *           on the stream or until the capture is terminated.
 * \param numDependencies_out - Optional location to store the size of the array
 *           returned in dependencies_out.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorStreamCaptureImplicit,
 * ::cudaErrorLossyQuery
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cudaStreamBeginCapture,
 * ::cudaStreamIsCapturing,
 * ::cudaStreamUpdateCaptureDependencies
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo(cudaStream_t stream,
    enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out __dv(0),
    cudaGraph_t *graph_out __dv(0), const cudaGraphNode_t **dependencies_out __dv(0),
    const cudaGraphEdgeData **edgeData_out __dv(0), size_t *numDependencies_out __dv(0));


/**
 * \brief Update the set of dependencies in a capturing stream
 *
 * Modifies the dependency set of a capturing stream. The dependency set is the set
 * of nodes that the next captured node in the stream will depend on.
 *
 * Valid flags are ::cudaStreamAddCaptureDependencies and
 * ::cudaStreamSetCaptureDependencies. These control whether the set passed to
 * the API is added to the existing set or replaces it. A flags value of 0 defaults
 * to ::cudaStreamAddCaptureDependencies.
 *
 * Nodes that are removed from the dependency set via this API do not result in
 * ::cudaErrorStreamCaptureUnjoined if they are unreachable from the stream at
 * ::cudaStreamEndCapture.
 *
 * Returns ::cudaErrorIllegalState if the stream is not capturing.
 *
 * \param stream - The stream to update
 * \param dependencies - The set of dependencies to add
 * \param dependencyData - Optional array of data associated with each dependency.
 * \param numDependencies - The size of the dependencies array
 * \param flags - See above
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorIllegalState
 * \notefnerr
 *
 * \sa
 * ::cudaStreamBeginCapture,
 * ::cudaStreamGetCaptureInfo,
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamUpdateCaptureDependencies(cudaStream_t stream, cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, unsigned int flags __dv(0));
/** @} */ /* END CUDART_STREAM */

/**
 * \defgroup CUDART_EVENT Event Management
 *
 * ___MANBRIEF___ event management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the event management functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Creates an event object
 *
 * Creates an event object for the current device using ::cudaEventDefault.
 *
 * \param event - Newly created event
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*, unsigned int) "cudaEventCreate (C++ API)",
 * ::cudaEventCreateWithFlags, ::cudaEventRecord, ::cudaEventQuery,
 * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime,
 * ::cudaStreamWaitEvent,
 * ::cuEventCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaEventCreate(cudaEvent_t *event);

/**
 * \brief Creates an event object with the specified flags
 *
 * Creates an event object for the current device with the specified flags. Valid
 * flags include:
 * - ::cudaEventDefault: Default event creation flag.
 * - ::cudaEventBlockingSync: Specifies that event should use blocking
 *   synchronization. A host thread that uses ::cudaEventSynchronize() to wait
 *   on an event created with this flag will block until the event actually
 *   completes.
 * - ::cudaEventDisableTiming: Specifies that the created event does not need
 *   to record timing data.  Events created with this flag specified and
 *   the ::cudaEventBlockingSync flag not specified will provide the best
 *   performance when used with ::cudaStreamWaitEvent() and ::cudaEventQuery().
 * - ::cudaEventInterprocess: Specifies that the created event may be used as an
 *   interprocess event by ::cudaIpcGetEventHandle(). ::cudaEventInterprocess must
 *   be specified along with ::cudaEventDisableTiming.
 *
 * \param event - Newly created event
 * \param flags - Flags for new event
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime,
 * ::cudaStreamWaitEvent,
 * ::cuEventCreate
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventCreateWithFlags(cudaEvent_t *event, unsigned int flags);

/**
 * \brief Records an event
 *
 * Captures in \p event the contents of \p stream at the time of this call.
 * \p event and \p stream must be on the same CUDA context.
 * Calls such as ::cudaEventQuery() or ::cudaStreamWaitEvent() will then
 * examine or wait for completion of the work that was captured. Uses of
 * \p stream after this call do not modify \p event. See note on default
 * stream behavior for what is captured in the default case.
 *
 * ::cudaEventRecord() can be called multiple times on the same event and
 * will overwrite the previously captured state. Other APIs such as
 * ::cudaStreamWaitEvent() use the most recently captured state at the time
 * of the API call, and are not affected by later calls to
 * ::cudaEventRecord(). Before the first call to ::cudaEventRecord(), an
 * event represents an empty set of work, so for example ::cudaEventQuery()
 * would return ::cudaSuccess.
 *
 * \param event  - Event to record
 * \param stream - Stream in which to record event
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorLaunchFailure
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_null_event
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventCreateWithFlags, ::cudaEventQuery,
 * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime,
 * ::cudaStreamWaitEvent,
 * ::cudaEventRecordWithFlags,
 * ::cuEventRecord
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecord(cudaEvent_t event, cudaStream_t stream __dv(0));

/**
 * \brief Records an event
 *
 * Captures in \p event the contents of \p stream at the time of this call.
 * \p event and \p stream must be on the same CUDA context.
 * Calls such as ::cudaEventQuery() or ::cudaStreamWaitEvent() will then
 * examine or wait for completion of the work that was captured. Uses of
 * \p stream after this call do not modify \p event. See note on default
 * stream behavior for what is captured in the default case.
 *
 * ::cudaEventRecordWithFlags() can be called multiple times on the same event and
 * will overwrite the previously captured state. Other APIs such as
 * ::cudaStreamWaitEvent() use the most recently captured state at the time
 * of the API call, and are not affected by later calls to
 * ::cudaEventRecordWithFlags(). Before the first call to ::cudaEventRecordWithFlags(), an
 * event represents an empty set of work, so for example ::cudaEventQuery()
 * would return ::cudaSuccess.
 *
 * flags include:
 * - ::cudaEventRecordDefault: Default event creation flag.
 * - ::cudaEventRecordExternal: Event is captured in the graph as an external
 *   event node when performing stream capture.
 *
 * \param event  - Event to record
 * \param stream - Stream in which to record event
 * \param flags  - Parameters for the operation(See above)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorLaunchFailure
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_null_event
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventCreateWithFlags, ::cudaEventQuery,
 * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime,
 * ::cudaStreamWaitEvent,
 * ::cudaEventRecord,
 * ::cuEventRecord,
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecordWithFlags(cudaEvent_t event, cudaStream_t stream __dv(0), unsigned int flags __dv(0));
#endif

/**
 * \brief Queries an event's status
 *
 * Queries the status of all work currently captured by \p event. See
 * ::cudaEventRecord() for details on what is captured by an event.
 *
 * Returns ::cudaSuccess if all captured work has been completed, or
 * ::cudaErrorNotReady if any captured work is incomplete.
 *
 * For the purposes of Unified Memory, a return value of ::cudaSuccess
 * is equivalent to having called ::cudaEventSynchronize().
 *
 * \param event - Event to query
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotReady,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorLaunchFailure
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_null_event
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventCreateWithFlags, ::cudaEventRecord,
 * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime,
 * ::cuEventQuery
 */
extern __host__ cudaError_t CUDARTAPI cudaEventQuery(cudaEvent_t event);

/**
 * \brief Waits for an event to complete
 *
 * Waits until the completion of all work currently captured in \p event.
 * See ::cudaEventRecord() for details on what is captured by an event.
 *
 * Waiting for an event that was created with the ::cudaEventBlockingSync
 * flag will cause the calling CPU thread to block until the event has
 * been completed by the device.  If the ::cudaEventBlockingSync flag has
 * not been set, then the CPU thread will busy-wait until the event has
 * been completed by the device.
 *
 * \param event - Event to wait for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorLaunchFailure
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_null_event
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventCreateWithFlags, ::cudaEventRecord,
 * ::cudaEventQuery, ::cudaEventDestroy, ::cudaEventElapsedTime,
 * ::cuEventSynchronize
 */
extern __host__ cudaError_t CUDARTAPI cudaEventSynchronize(cudaEvent_t event);

/**
 * \brief Destroys an event object
 *
 * Destroys the event specified by \p event.
 *
 * An event may be destroyed before it is complete (i.e., while
 * ::cudaEventQuery() would return ::cudaErrorNotReady). In this case, the
 * call does not block on completion of the event, and any associated
 * resources will automatically be released asynchronously at completion.
 *
 * \param event - Event to destroy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorLaunchFailure
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 * \note_null_event
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventCreateWithFlags, ::cudaEventQuery,
 * ::cudaEventSynchronize, ::cudaEventRecord, ::cudaEventElapsedTime,
 * ::cuEventDestroy
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventDestroy(cudaEvent_t event);

/**
 * \brief Computes the elapsed time between events
 *
 * Computes the elapsed time between two events (in milliseconds with a
 * resolution of around 0.5 microseconds). Note this API is not guaranteed
 * to return the latest errors for pending work. As such this API is intended to
 * serve as a elapsed time calculation only and polling for completion on the
 * events to be compared should be done with ::cudaEventQuery instead.
 *
 * If either event was last recorded in a non-NULL stream, the resulting time
 * may be greater than expected (even if both used the same stream handle). This
 * happens because the ::cudaEventRecord() operation takes place asynchronously
 * and there is no guarantee that the measured latency is actually just between
 * the two events. Any number of other different stream operations could execute
 * in between the two measured events, thus altering the timing in a significant
 * way.
 *
 * If ::cudaEventRecord() has not been called on either event, then
 * ::cudaErrorInvalidResourceHandle is returned. If ::cudaEventRecord() has been
 * called on both events but one or both of them has not yet been completed
 * (that is, ::cudaEventQuery() would return ::cudaErrorNotReady on at least one
 * of the events), ::cudaErrorNotReady is returned. If either event was created
 * with the ::cudaEventDisableTiming flag, then this function will return
 * ::cudaErrorInvalidResourceHandle.
 *
 * \param ms    - Time between \p start and \p end in ms
 * \param start - Starting event
 * \param end   - Ending event
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotReady,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorUnknown
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_null_event
 *
 * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)",
 * ::cudaEventCreateWithFlags, ::cudaEventQuery,
 * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventRecord,
 * ::cuEventElapsedTime
 */
extern __host__ cudaError_t CUDARTAPI cudaEventElapsedTime(float *ms, cudaEvent_t start, cudaEvent_t end);

/** @} */ /* END CUDART_EVENT */

/**
 * \defgroup CUDART_EXTRES_INTEROP External Resource Interoperability
 *
 * ___MANBRIEF___ External resource interoperability functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the external resource interoperability functions of the CUDA
 * runtime application programming interface.
 *
 * @{
 */

/**
 * \brief Imports an external memory object
 *
 * Imports an externally allocated memory object and returns
 * a handle to that in \p extMem_out.
 *
 * The properties of the handle being imported must be described in
 * \p memHandleDesc. The ::cudaExternalMemoryHandleDesc structure
 * is defined as follows:
 *
 * \code
        typedef struct cudaExternalMemoryHandleDesc_st {
            cudaExternalMemoryHandleType type;
            union {
                int fd;
                struct {
                    void *handle;
                    const void *name;
                } win32;
                const void *nvSciBufObject;
            } handle;
            unsigned long long size;
            unsigned int flags;
        } cudaExternalMemoryHandleDesc;
 * \endcode
 *
 * where ::cudaExternalMemoryHandleDesc::type specifies the type
 * of handle being imported. ::cudaExternalMemoryHandleType is
 * defined as:
 *
 * \code
        typedef enum cudaExternalMemoryHandleType_enum {
            cudaExternalMemoryHandleTypeOpaqueFd         = 1,
            cudaExternalMemoryHandleTypeOpaqueWin32      = 2,
            cudaExternalMemoryHandleTypeOpaqueWin32Kmt   = 3,
            cudaExternalMemoryHandleTypeD3D12Heap        = 4,
            cudaExternalMemoryHandleTypeD3D12Resource    = 5,
	        cudaExternalMemoryHandleTypeD3D11Resource    = 6,
		    cudaExternalMemoryHandleTypeD3D11ResourceKmt = 7,
            cudaExternalMemoryHandleTypeNvSciBuf         = 8
        } cudaExternalMemoryHandleType;
 * \endcode
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeOpaqueFd, then
 * ::cudaExternalMemoryHandleDesc::handle::fd must be a valid
 * file descriptor referencing a memory object. Ownership of
 * the file descriptor is transferred to the CUDA driver when the
 * handle is imported successfully. Performing any operations on the
 * file descriptor after it is imported results in undefined behavior.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeOpaqueWin32, then exactly one
 * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and
 * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * references a memory object. Ownership of this handle is
 * not transferred to CUDA after the import operation, so the
 * application must release the handle using the appropriate system
 * call. If ::cudaExternalMemoryHandleDesc::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a memory object.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeOpaqueWin32Kmt, then
 * ::cudaExternalMemoryHandleDesc::handle::win32::handle must
 * be non-NULL and
 * ::cudaExternalMemoryHandleDesc::handle::win32::name
 * must be NULL. The handle specified must be a globally shared KMT
 * handle. This handle does not hold a reference to the underlying
 * object, and thus will be invalid when all references to the
 * memory object are destroyed.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeD3D12Heap, then exactly one
 * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and
 * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D12Device::CreateSharedHandle when referring to a
 * ID3D12Heap object. This handle holds a reference to the underlying
 * object. If ::cudaExternalMemoryHandleDesc::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a ID3D12Heap object.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeD3D12Resource, then exactly one
 * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and
 * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D12Device::CreateSharedHandle when referring to a
 * ID3D12Resource object. This handle holds a reference to the
 * underlying object. If
 * ::cudaExternalMemoryHandleDesc::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a ID3D12Resource object.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeD3D11Resource,then exactly one
 * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and
 * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle is    
 * not NULL, then it must represent a valid shared NT handle that is  
 * returned by  IDXGIResource1::CreateSharedHandle when referring to a 
 * ID3D11Resource object. If
 * ::cudaExternalMemoryHandleDesc::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a ID3D11Resource object.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeD3D11ResourceKmt, then
 * ::cudaExternalMemoryHandleDesc::handle::win32::handle must
 * be non-NULL and ::cudaExternalMemoryHandleDesc::handle::win32::name
 * must be NULL. The handle specified must be a valid shared KMT
 * handle that is returned by IDXGIResource::GetSharedHandle when
 * referring to a ID3D11Resource object.
 *
 * If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeNvSciBuf, then
 * ::cudaExternalMemoryHandleDesc::handle::nvSciBufObject must be NON-NULL
 * and reference a valid NvSciBuf object.
 * If the NvSciBuf object imported into CUDA is also mapped by other drivers, then the
 * application must use ::cudaWaitExternalSemaphoresAsync or ::cudaSignalExternalSemaphoresAsync
 * as approprriate barriers to maintain coherence between CUDA and the other drivers.
 * See ::cudaExternalSemaphoreWaitSkipNvSciBufMemSync and ::cudaExternalSemaphoreSignalSkipNvSciBufMemSync 
 * for memory synchronization.
 *
 * The size of the memory object must be specified in
 * ::cudaExternalMemoryHandleDesc::size.
 *
 * Specifying the flag ::cudaExternalMemoryDedicated in
 * ::cudaExternalMemoryHandleDesc::flags indicates that the
 * resource is a dedicated resource. The definition of what a
 * dedicated resource is outside the scope of this extension.
 * This flag must be set if ::cudaExternalMemoryHandleDesc::type
 * is one of the following:
 * ::cudaExternalMemoryHandleTypeD3D12Resource
 * ::cudaExternalMemoryHandleTypeD3D11Resource
 * ::cudaExternalMemoryHandleTypeD3D11ResourceKmt
 *
 * \param extMem_out    - Returned handle to an external memory object
 * \param memHandleDesc - Memory import handle descriptor
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorOperatingSystem
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \note If the Vulkan memory imported into CUDA is mapped on the CPU then the
 * application must use vkInvalidateMappedMemoryRanges/vkFlushMappedMemoryRanges
 * as well as appropriate Vulkan pipeline barriers to maintain coherence between
 * CPU and GPU. For more information on these APIs, please refer to "Synchronization
 * and Cache Control" chapter from Vulkan specification.
 *
 *
 * \sa ::cudaDestroyExternalMemory,
 * ::cudaExternalMemoryGetMappedBuffer,
 * ::cudaExternalMemoryGetMappedMipmappedArray
 */
extern __host__ cudaError_t CUDARTAPI cudaImportExternalMemory(cudaExternalMemory_t *extMem_out, const struct cudaExternalMemoryHandleDesc *memHandleDesc);

/**
 * \brief Maps a buffer onto an imported memory object
 *
 * Maps a buffer onto an imported memory object and returns a device
 * pointer in \p devPtr.
 *
 * The properties of the buffer being mapped must be described in
 * \p bufferDesc. The ::cudaExternalMemoryBufferDesc structure is
 * defined as follows:
 *
 * \code
        typedef struct cudaExternalMemoryBufferDesc_st {
            unsigned long long offset;
            unsigned long long size;
            unsigned int flags;
        } cudaExternalMemoryBufferDesc;
 * \endcode
 *
 * where ::cudaExternalMemoryBufferDesc::offset is the offset in
 * the memory object where the buffer's base address is.
 * ::cudaExternalMemoryBufferDesc::size is the size of the buffer.
 * ::cudaExternalMemoryBufferDesc::flags must be zero.
 *
 * The offset and size have to be suitably aligned to match the
 * requirements of the external API. Mapping two buffers whose ranges
 * overlap may or may not result in the same virtual address being
 * returned for the overlapped portion. In such cases, the application
 * must ensure that all accesses to that region from the GPU are
 * volatile. Otherwise writes made via one address are not guaranteed
 * to be visible via the other address, even if they're issued by the
 * same thread. It is recommended that applications map the combined
 * range instead of mapping separate buffers and then apply the
 * appropriate offsets to the returned pointer to derive the
 * individual buffers.
 *
 * The returned pointer \p devPtr must be freed using ::cudaFree.
 *
 * \param devPtr     - Returned device pointer to buffer
 * \param extMem     - Handle to external memory object
 * \param bufferDesc - Buffer descriptor
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaImportExternalMemory,
 * ::cudaDestroyExternalMemory,
 * ::cudaExternalMemoryGetMappedMipmappedArray
 */
extern __host__ cudaError_t CUDARTAPI cudaExternalMemoryGetMappedBuffer(void **devPtr, cudaExternalMemory_t extMem, const struct cudaExternalMemoryBufferDesc *bufferDesc);

/**
 * \brief Maps a CUDA mipmapped array onto an external memory object
 *
 * Maps a CUDA mipmapped array onto an external object and returns a
 * handle to it in \p mipmap.
 *
 * The properties of the CUDA mipmapped array being mapped must be
 * described in \p mipmapDesc. The structure
 * ::cudaExternalMemoryMipmappedArrayDesc is defined as follows:
 *
 * \code
        typedef struct cudaExternalMemoryMipmappedArrayDesc_st {
            unsigned long long offset;
            cudaChannelFormatDesc formatDesc;
            cudaExtent extent;
            unsigned int flags;
            unsigned int numLevels;
        } cudaExternalMemoryMipmappedArrayDesc;
 * \endcode
 *
 * where ::cudaExternalMemoryMipmappedArrayDesc::offset is the
 * offset in the memory object where the base level of the mipmap
 * chain is.
 * ::cudaExternalMemoryMipmappedArrayDesc::formatDesc describes the
 * format of the data.
 * ::cudaExternalMemoryMipmappedArrayDesc::extent specifies the
 * dimensions of the base level of the mipmap chain.
 * ::cudaExternalMemoryMipmappedArrayDesc::flags are flags associated
 * with CUDA mipmapped arrays. For further details, please refer to
 * the documentation for ::cudaMalloc3DArray. Note that if the mipmapped
 * array is bound as a color target in the graphics API, then the flag
 * ::cudaArrayColorAttachment must be specified in 
 * ::cudaExternalMemoryMipmappedArrayDesc::flags.
 * ::cudaExternalMemoryMipmappedArrayDesc::numLevels specifies
 * the total number of levels in the mipmap chain.
 *
 * The returned CUDA mipmapped array must be freed using ::cudaFreeMipmappedArray.
 *
 * \param mipmap     - Returned CUDA mipmapped array
 * \param extMem     - Handle to external memory object
 * \param mipmapDesc - CUDA array descriptor
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaImportExternalMemory,
 * ::cudaDestroyExternalMemory,
 * ::cudaExternalMemoryGetMappedBuffer
 *
 * \note If ::cudaExternalMemoryHandleDesc::type is
 * ::cudaExternalMemoryHandleTypeNvSciBuf, then
 * ::cudaExternalMemoryMipmappedArrayDesc::numLevels must not be greater than 1.
 */
extern __host__ cudaError_t CUDARTAPI cudaExternalMemoryGetMappedMipmappedArray(cudaMipmappedArray_t *mipmap, cudaExternalMemory_t extMem, const struct cudaExternalMemoryMipmappedArrayDesc *mipmapDesc);

/**
 * \brief Destroys an external memory object.
 *
 * Destroys the specified external memory object. Any existing buffers
 * and CUDA mipmapped arrays mapped onto this object must no longer be
 * used and must be explicitly freed using ::cudaFree and
 * ::cudaFreeMipmappedArray respectively.
 *
 * \param extMem - External memory object to be destroyed
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa ::cudaImportExternalMemory,
 * ::cudaExternalMemoryGetMappedBuffer,
 * ::cudaExternalMemoryGetMappedMipmappedArray
 */
extern __host__ cudaError_t CUDARTAPI cudaDestroyExternalMemory(cudaExternalMemory_t extMem);

/**
 * \brief Imports an external semaphore
 *
 * Imports an externally allocated synchronization object and returns
 * a handle to that in \p extSem_out.
 *
 * The properties of the handle being imported must be described in
 * \p semHandleDesc. The ::cudaExternalSemaphoreHandleDesc is defined
 * as follows:
 *
 * \code
        typedef struct cudaExternalSemaphoreHandleDesc_st {
            cudaExternalSemaphoreHandleType type;
            union {
                int fd;
                struct {
                    void *handle;
                    const void *name;
                } win32;
                const void* NvSciSyncObj;
            } handle;
            unsigned int flags;
        } cudaExternalSemaphoreHandleDesc;
 * \endcode
 *
 * where ::cudaExternalSemaphoreHandleDesc::type specifies the type of
 * handle being imported. ::cudaExternalSemaphoreHandleType is defined
 * as:
 *
 * \code
        typedef enum cudaExternalSemaphoreHandleType_enum {
            cudaExternalSemaphoreHandleTypeOpaqueFd                = 1,
            cudaExternalSemaphoreHandleTypeOpaqueWin32             = 2,
            cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt          = 3,
            cudaExternalSemaphoreHandleTypeD3D12Fence              = 4,
            cudaExternalSemaphoreHandleTypeD3D11Fence              = 5,
            cudaExternalSemaphoreHandleTypeNvSciSync               = 6,
            cudaExternalSemaphoreHandleTypeKeyedMutex              = 7,
            cudaExternalSemaphoreHandleTypeKeyedMutexKmt           = 8,
            cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd     = 9,
            cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32  = 10
        } cudaExternalSemaphoreHandleType;
 * \endcode
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeOpaqueFd, then
 * ::cudaExternalSemaphoreHandleDesc::handle::fd must be a valid file
 * descriptor referencing a synchronization object. Ownership of the
 * file descriptor is transferred to the CUDA driver when the handle
 * is imported successfully. Performing any operations on the file
 * descriptor after it is imported results in undefined behavior.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeOpaqueWin32, then exactly one of
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * references a synchronization object. Ownership of this handle is
 * not transferred to CUDA after the import operation, so the
 * application must release the handle using the appropriate system
 * call. If ::cudaExternalSemaphoreHandleDesc::handle::win32::name is
 * not NULL, then it must name a valid synchronization object.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt, then
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle must be
 * non-NULL and ::cudaExternalSemaphoreHandleDesc::handle::win32::name
 * must be NULL. The handle specified must be a globally shared KMT
 * handle. This handle does not hold a reference to the underlying
 * object, and thus will be invalid when all references to the
 * synchronization object are destroyed.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeD3D12Fence, then exactly one of
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D12Device::CreateSharedHandle when referring to a
 * ID3D12Fence object. This handle holds a reference to the underlying
 * object. If ::cudaExternalSemaphoreHandleDesc::handle::win32::name
 * is not NULL, then it must name a valid synchronization object that
 * refers to a valid ID3D12Fence object.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeD3D11Fence, then exactly one of
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D11Fence::CreateSharedHandle. If 
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::name
 * is not NULL, then it must name a valid synchronization object that
 * refers to a valid ID3D11Fence object.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeNvSciSync, then
 * ::cudaExternalSemaphoreHandleDesc::handle::nvSciSyncObj
 * represents a valid NvSciSyncObj.
 *
 * ::cudaExternalSemaphoreHandleTypeKeyedMutex, then exactly one of
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle
 * is not NULL, then it represent a valid shared NT handle that
 * is returned by IDXGIResource1::CreateSharedHandle when referring to
 * a IDXGIKeyedMutex object.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeKeyedMutexKmt, then
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle must be
 * non-NULL and ::cudaExternalSemaphoreHandleDesc::handle::win32::name
 * must be NULL. The handle specified must represent a valid KMT
 * handle that is returned by IDXGIResource::GetSharedHandle when
 * referring to a IDXGIKeyedMutex object.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd, then
 * ::cudaExternalSemaphoreHandleDesc::handle::fd must be a valid file
 * descriptor referencing a synchronization object. Ownership of the
 * file descriptor is transferred to the CUDA driver when the handle
 * is imported successfully. Performing any operations on the file
 * descriptor after it is imported results in undefined behavior.
 *
 * If ::cudaExternalSemaphoreHandleDesc::type is
 * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32, then exactly one of
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and
 * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be
 * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * references a synchronization object. Ownership of this handle is
 * not transferred to CUDA after the import operation, so the
 * application must release the handle using the appropriate system
 * call. If ::cudaExternalSemaphoreHandleDesc::handle::win32::name is
 * not NULL, then it must name a valid synchronization object.
 *
 * \param extSem_out    - Returned handle to an external semaphore
 * \param semHandleDesc - Semaphore import handle descriptor
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorOperatingSystem
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDestroyExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaImportExternalSemaphore(cudaExternalSemaphore_t *extSem_out, const struct cudaExternalSemaphoreHandleDesc *semHandleDesc);

/**
 * \brief Signals a set of external semaphore objects
 *
 * Enqueues a signal operation on a set of externally allocated
 * semaphore object in the specified stream. The operations will be
 * executed when all prior operations in the stream complete.
 *
 * The exact semantics of signaling a semaphore depends on the type of
 * the object.
 *
 * If the semaphore object is any one of the following types:
 * ::cudaExternalSemaphoreHandleTypeOpaqueFd,
 * ::cudaExternalSemaphoreHandleTypeOpaqueWin32,
 * ::cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt
 * then signaling the semaphore will set it to the signaled state.
 *
 * If the semaphore object is any one of the following types:
 * ::cudaExternalSemaphoreHandleTypeD3D12Fence,
 * ::cudaExternalSemaphoreHandleTypeD3D11Fence,
 * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd,
 * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32
 * then the semaphore will be set to the value specified in
 * ::cudaExternalSemaphoreSignalParams::params::fence::value.
 *
 * If the semaphore object is of the type ::cudaExternalSemaphoreHandleTypeNvSciSync
 * this API sets ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence to a
 * value that can be used by subsequent waiters of the same NvSciSync object to
 * order operations with those currently submitted in \p stream. Such an update
 * will overwrite previous contents of
 * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence. By default,
 * signaling such an external semaphore object causes appropriate memory synchronization
 * operations to be performed over all the external memory objects that are imported as
 * ::cudaExternalMemoryHandleTypeNvSciBuf. This ensures that any subsequent accesses
 * made by other importers of the same set of NvSciBuf memory object(s) are coherent.
 * These operations can be skipped by specifying the flag
 * ::cudaExternalSemaphoreSignalSkipNvSciBufMemSync, which can be used as a
 * performance optimization when data coherency is not required. But specifying this
 * flag in scenarios where data coherency is required results in undefined behavior.
 * Also, for semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync,
 * if the NvSciSyncAttrList used to create the NvSciSyncObj had not set the flags in
 * ::cudaDeviceGetNvSciSyncAttributes to cudaNvSciSyncAttrSignal, this API will return
 * cudaErrorNotSupported.
 * 
 * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence associated with 
 * semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync can be 
 * deterministic. For this the NvSciSyncAttrList used to create the semaphore object 
 * must have value of NvSciSyncAttrKey_RequireDeterministicFences key set to true. 
 * Deterministic fences allow users to enqueue a wait over the semaphore object even 
 * before corresponding signal is enqueued. For such a semaphore object, CUDA guarantees 
 * that each signal operation will increment the fence value by '1'. Users are expected 
 * to track count of signals enqueued on the semaphore object and insert waits accordingly. 
 * When such a semaphore object is signaled from multiple streams, due to concurrent 
 * stream execution, it is possible that the order in which the semaphore gets signaled 
 * is indeterministic. This could lead to waiters of the semaphore getting unblocked 
 * incorrectly. Users are expected to handle such situations, either by not using the 
 * same semaphore object with deterministic fence support enabled in different streams 
 * or by adding explicit dependency amongst such streams so that the semaphore is 
 * signaled in order.
 * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence associated with
 * semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync can be
 * timestamp enabled. For this the NvSciSyncAttrList used to create the object must
 * have the value of NvSciSyncAttrKey_WaiterRequireTimestamps key set to true. Timestamps
 * are emitted asynchronously by the GPU and CUDA saves the GPU timestamp in the
 * corresponding NvSciSyncFence at the time of signal on GPU. Users are expected to 
 * convert GPU clocks to CPU clocks using appropriate scaling functions. Users are 
 * expected to wait for the completion of the fence before extracting timestamp using 
 * appropriate NvSciSync APIs. Users are expected to ensure that there is only one 
 * outstanding timestamp enabled fence per Cuda-NvSciSync object at any point of time, 
 * failing which leads to undefined behavior. Extracting the timestamp before the
 * corresponding fence is signalled could lead to undefined behaviour. Timestamp 
 * extracted via appropriate NvSciSync API would be in microseconds.
 *
 * If the semaphore object is any one of the following types:
 * ::cudaExternalSemaphoreHandleTypeKeyedMutex,
 * ::cudaExternalSemaphoreHandleTypeKeyedMutexKmt,
 * then the keyed mutex will be released with the key specified in
 * ::cudaExternalSemaphoreSignalParams::params::keyedmutex::key.
 *
 * \param extSemArray - Set of external semaphores to be signaled
 * \param paramsArray - Array of semaphore parameters
 * \param numExtSems  - Number of semaphores to signal
 * \param stream     - Stream to enqueue the signal operations in
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaImportExternalSemaphore,
 * ::cudaDestroyExternalSemaphore,
 * ::cudaWaitExternalSemaphoresAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaSignalExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreSignalParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0));

/**
 * \brief Waits on a set of external semaphore objects
 *
 * Enqueues a wait operation on a set of externally allocated
 * semaphore object in the specified stream. The operations will be
 * executed when all prior operations in the stream complete.
 *
 * The exact semantics of waiting on a semaphore depends on the type
 * of the object.
 *
 * If the semaphore object is any one of the following types:
 * ::cudaExternalSemaphoreHandleTypeOpaqueFd,
 * ::cudaExternalSemaphoreHandleTypeOpaqueWin32,
 * ::cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt
 * then waiting on the semaphore will wait until the semaphore reaches
 * the signaled state. The semaphore will then be reset to the
 * unsignaled state. Therefore for every signal operation, there can
 * only be one wait operation.
 *
 * If the semaphore object is any one of the following types:
 * ::cudaExternalSemaphoreHandleTypeD3D12Fence,
 * ::cudaExternalSemaphoreHandleTypeD3D11Fence,
 * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd,
 * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32
 * then waiting on the semaphore will wait until the value of the
 * semaphore is greater than or equal to
 * ::cudaExternalSemaphoreWaitParams::params::fence::value.
 *
 * If the semaphore object is of the type ::cudaExternalSemaphoreHandleTypeNvSciSync
 * then, waiting on the semaphore will wait until the
 * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence is signaled by the
 * signaler of the NvSciSyncObj that was associated with this semaphore object.
 * By default, waiting on such an external semaphore object causes appropriate
 * memory synchronization operations to be performed over all external memory objects
 * that are imported as ::cudaExternalMemoryHandleTypeNvSciBuf. This ensures that
 * any subsequent accesses made by other importers of the same set of NvSciBuf memory
 * object(s) are coherent. These operations can be skipped by specifying the flag
 * ::cudaExternalSemaphoreWaitSkipNvSciBufMemSync, which can be used as a
 * performance optimization when data coherency is not required. But specifying this
 * flag in scenarios where data coherency is required results in undefined behavior.
 * Also, for semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync,
 * if the NvSciSyncAttrList used to create the NvSciSyncObj had not set the flags in
 * ::cudaDeviceGetNvSciSyncAttributes to cudaNvSciSyncAttrWait, this API will return
 * cudaErrorNotSupported.
 *
 * If the semaphore object is any one of the following types:
 * ::cudaExternalSemaphoreHandleTypeKeyedMutex,
 * ::cudaExternalSemaphoreHandleTypeKeyedMutexKmt,
 * then the keyed mutex will be acquired when it is released with the key specified 
 * in ::cudaExternalSemaphoreSignalParams::params::keyedmutex::key or
 * until the timeout specified by
 * ::cudaExternalSemaphoreSignalParams::params::keyedmutex::timeoutMs
 * has lapsed. The timeout interval can either be a finite value
 * specified in milliseconds or an infinite value. In case an infinite
 * value is specified the timeout never elapses. The windows INFINITE
 * macro must be used to specify infinite timeout
 *
 * \param extSemArray - External semaphores to be waited on
 * \param paramsArray - Array of semaphore parameters
 * \param numExtSems  - Number of semaphores to wait on
 * \param stream      - Stream to enqueue the wait operations in
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle
 * ::cudaErrorTimeout
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaImportExternalSemaphore,
 * ::cudaDestroyExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaWaitExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreWaitParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0));

/**
 * \brief Destroys an external semaphore
 *
 * Destroys an external semaphore object and releases any references
 * to the underlying resource. Any outstanding signals or waits must
 * have completed before the semaphore is destroyed.
 *
 * \param extSem - External semaphore to be destroyed
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa ::cudaImportExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaDestroyExternalSemaphore(cudaExternalSemaphore_t extSem);

/** @} */ /* END CUDART_EXTRES_INTEROP */

/**
 * \defgroup CUDART_EXECUTION Execution Control
 *
 * ___MANBRIEF___ execution control functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the execution control functions of the CUDA runtime
 * application programming interface.
 *
 * Some functions have overloaded C++ API template versions documented separately in the
 * \ref CUDART_HIGHLEVEL "C++ API Routines" module.
 *
 * @{
 */

/**
 * \brief Launches a device function
 *
 * The function invokes kernel \p func on \p gridDim (\p gridDim.x &times; \p gridDim.y
 * &times; \p gridDim.z) grid of blocks. Each block contains \p blockDim (\p blockDim.x &times;
 * \p blockDim.y &times; \p blockDim.z) threads.
 *
 * If the kernel has N parameters the \p args should point to array of N pointers.
 * Each pointer, from <tt>args[0]</tt> to <tt>args[N - 1]</tt>, point to the region
 * of memory from which the actual parameter will be copied.
 *
 * For templated functions, pass the function symbol as follows:
 * func_name<template_arg_0,...,template_arg_N>
 *
 * \p sharedMem sets the amount of dynamic shared memory that will be available to
 * each thread block.
 *
 * \p stream specifies a stream the invocation is associated to.
 *
 * \param func        - Device function symbol
 * \param gridDim     - Grid dimentions
 * \param blockDim    - Block dimentions
 * \param args        - Arguments
 * \param sharedMem   - Shared memory
 * \param stream      - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidConfiguration,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorLaunchTimeout,
 * ::cudaErrorLaunchOutOfResources,
 * ::cudaErrorSharedObjectInitFailed,
 * ::cudaErrorInvalidPtx,
 * ::cudaErrorUnsupportedPtxVersion,
 * ::cudaErrorNoKernelImageForDevice,
 * ::cudaErrorJitCompilerNotFound,
 * ::cudaErrorJitCompilationDisabled
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * \ref ::cudaLaunchKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C++ API)",
 * ::cuLaunchKernel
 */
extern __host__ cudaError_t CUDARTAPI cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream);

/**
 * \brief Launches a CUDA function with launch-time configuration
 *
 * Note that the functionally equivalent variadic template ::cudaLaunchKernelEx
 * is available for C++11 and newer.
 *
 * Invokes the kernel \p func on \p config->gridDim (\p config->gridDim.x
 * &times; \p config->gridDim.y &times; \p config->gridDim.z) grid of blocks.
 * Each block contains \p config->blockDim (\p config->blockDim.x &times;
 * \p config->blockDim.y &times; \p config->blockDim.z) threads.
 *
 * \p config->dynamicSmemBytes sets the amount of dynamic shared memory that
 * will be available to each thread block.
 *
 * \p config->stream specifies a stream the invocation is associated to.
 *
 * Configuration beyond grid and block dimensions, dynamic shared memory size,
 * and stream can be provided with the following two fields of \p config:
 *
 * \p config->attrs is an array of \p config->numAttrs contiguous
 * ::cudaLaunchAttribute elements. The value of this pointer is not considered
 * if \p config->numAttrs is zero. However, in that case, it is recommended to
 * set the pointer to NULL.                                  
 * \p config->numAttrs is the number of attributes populating the first
 * \p config->numAttrs positions of the \p config->attrs array.
 *
 * If the kernel has N parameters the \p args should point to array of N
 * pointers. Each pointer, from <tt>args[0]</tt> to <tt>args[N - 1]</tt>, point
 * to the region of memory from which the actual parameter will be copied.
 *
 * N.B. This function is so named to avoid unintentionally invoking the
 *      templated version, \p cudaLaunchKernelEx, for kernels taking a single
 *      void** or void* parameter.
 *
 * \param config - Launch configuration
 * \param func   - Kernel to launch
 * \param args   - Array of pointers to kernel parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidConfiguration,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorLaunchTimeout,
 * ::cudaErrorLaunchOutOfResources,
 * ::cudaErrorSharedObjectInitFailed,
 * ::cudaErrorInvalidPtx,
 * ::cudaErrorUnsupportedPtxVersion,
 * ::cudaErrorNoKernelImageForDevice,
 * ::cudaErrorJitCompilerNotFound,
 * ::cudaErrorJitCompilationDisabled
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * \ref ::cudaLaunchKernelEx(const cudaLaunchConfig_t *config, void (*kernel)(ExpTypes...), ActTypes &&... args) "cudaLaunchKernelEx (C++ API)",
 * ::cuLaunchKernelEx
 */
extern __host__ cudaError_t CUDARTAPI cudaLaunchKernelExC(const cudaLaunchConfig_t *config, const void *func, void **args);

/**
 * \brief Launches a device function where thread blocks can cooperate and synchronize as they execute
 *
 * The function invokes kernel \p func on \p gridDim (\p gridDim.x &times; \p gridDim.y
 * &times; \p gridDim.z) grid of blocks. Each block contains \p blockDim (\p blockDim.x &times;
 * \p blockDim.y &times; \p blockDim.z) threads.
 *
 * The device on which this kernel is invoked must have a non-zero value for
 * the device attribute ::cudaDevAttrCooperativeLaunch.
 *
 * The total number of blocks launched cannot exceed the maximum number of blocks per
 * multiprocessor as returned by ::cudaOccupancyMaxActiveBlocksPerMultiprocessor (or
 * ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags) times the number of multiprocessors
 * as specified by the device attribute ::cudaDevAttrMultiProcessorCount.
 *
 * The kernel cannot make use of CUDA dynamic parallelism.
 *
 * If the kernel has N parameters the \p args should point to array of N pointers.
 * Each pointer, from <tt>args[0]</tt> to <tt>args[N - 1]</tt>, point to the region
 * of memory from which the actual parameter will be copied.
 *
 * For templated functions, pass the function symbol as follows:
 * func_name<template_arg_0,...,template_arg_N>
 *
 * \p sharedMem sets the amount of dynamic shared memory that will be available to
 * each thread block.
 *
 * \p stream specifies a stream the invocation is associated to.
 *
 * \param func        - Device function symbol
 * \param gridDim     - Grid dimentions
 * \param blockDim    - Block dimentions
 * \param args        - Arguments
 * \param sharedMem   - Shared memory
 * \param stream      - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidConfiguration,
 * ::cudaErrorLaunchFailure,
 * ::cudaErrorLaunchTimeout,
 * ::cudaErrorLaunchOutOfResources,
 * ::cudaErrorCooperativeLaunchTooLarge,
 * ::cudaErrorSharedObjectInitFailed
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * \ref ::cudaLaunchCooperativeKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchCooperativeKernel (C++ API)",
 * ::cuLaunchCooperativeKernel
 */
extern __host__ cudaError_t CUDARTAPI cudaLaunchCooperativeKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream);

/**
 * \brief Sets the preferred cache configuration for a device function
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this sets through \p cacheConfig the preferred cache configuration
 * for the function specified via \p func. This is only a preference. The
 * runtime will use the requested configuration if possible, but it is free to
 * choose a different configuration if required to execute \p func.
 *
 * \p func is a device function symbol and must be declared as a
 * \c __global__ function. If the specified function does not exist,
 * then ::cudaErrorInvalidDeviceFunction is returned. For templated functions,
 * pass the function symbol as follows: func_name<template_arg_0,...,template_arg_N>
 *
 * This setting does nothing on devices where the size of the L1 cache and
 * shared memory are fixed.
 *
 * Launching a kernel with a different preference than the most recent
 * preference setting may insert a device-side synchronization point.
 *
 * The supported cache configurations are:
 * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default)
 * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache
 * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory
 * - ::cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory
 *
 * \param func        - Device function symbol
 * \param cacheConfig - Requested cache configuration
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction
 * \notefnerr
 * \note_string_api_deprecation2
 * \note_init_rt
 * \note_callback
 *
 * \note This API does not accept a ::cudaKernel_t casted as void*. If cache config modification
 * is required for a ::cudaKernel_t (or a __global__ function), it can be replaced with a call to 
 * ::cudaFuncSetAttributes with the attribute ::cudaFuncAttributePreferredSharedMemoryCarveout 
 * to specify a more granular L1 cache and shared memory split configuration.
 *
 * \sa 
 * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)",
 * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const void*) "cudaFuncGetAttributes (C API)",
 * \ref ::cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C API)",
 * ::cuFuncSetCacheConfig
 */
extern __host__ cudaError_t CUDARTAPI cudaFuncSetCacheConfig(const void *func, enum cudaFuncCache cacheConfig);

/**
 * \brief Find out attributes for a given function
 *
 * This function obtains the attributes of a function specified via \p func.
 * \p func is a device function symbol and must be declared as a
 * \c __global__ function. The fetched attributes are placed in \p attr.
 * If the specified function does not exist, then it is assumed to 
 * be a ::cudaKernel_t and used as is.
 * For templated functions, pass the function symbol as follows: 
 * func_name<template_arg_0,...,template_arg_N>
 *
 * Note that some function attributes such as
 * \ref ::cudaFuncAttributes::maxThreadsPerBlock "maxThreadsPerBlock"
 * may vary based on the device that is currently being used.
 *
 * \param attr - Return pointer to function's attributes
 * \param func - Device function symbol
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction
 * \notefnerr
 * \note_string_api_deprecation2
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa 
 * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)",
 * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, T*) "cudaFuncGetAttributes (C++ API)",
 * \ref ::cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C API)",
 * ::cuFuncGetAttribute
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetAttributes(struct cudaFuncAttributes *attr, const void *func);


/**
 * \brief Set attributes for a given function
 *
 * This function sets the attributes of a function specified via \p func.
 * The parameter \p func must be a pointer to a function that executes
 * on the device. The parameter specified by \p func must be declared as a \p __global__
 * function. The enumeration defined by \p attr is set to the value defined by \p value.
 * If the specified function does not exist, then it is assumed to 
 * be a ::cudaKernel_t and used as is.
 * If the specified attribute cannot be written, or if the value is incorrect, 
 * then ::cudaErrorInvalidValue is returned.
 *
 * Valid values for \p attr are:
 * - ::cudaFuncAttributeMaxDynamicSharedMemorySize - The requested maximum size in bytes of dynamically-allocated shared memory. The sum of this value and the function attribute ::sharedSizeBytes
 *   cannot exceed the device attribute ::cudaDevAttrMaxSharedMemoryPerBlockOptin. The maximal size of requestable dynamic shared memory may differ by GPU architecture.
 * - ::cudaFuncAttributePreferredSharedMemoryCarveout - On devices where the L1 cache and shared memory use the same hardware resources, 
 *   this sets the shared memory carveout preference, in percent of the total shared memory. See ::cudaDevAttrMaxSharedMemoryPerMultiprocessor.
 *   This is only a hint, and the driver can choose a different ratio if required to execute the function.
 * - ::cudaFuncAttributeRequiredClusterWidth: The required cluster width in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return cudaErrorNotPermitted.
 * - ::cudaFuncAttributeRequiredClusterHeight: The required cluster height in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return cudaErrorNotPermitted.
 * - ::cudaFuncAttributeRequiredClusterDepth: The required cluster depth in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return cudaErrorNotPermitted.
 * - ::cudaFuncAttributeNonPortableClusterSizeAllowed: Indicates whether the
 *   function can be launched with non-portable cluster size. 1 is allowed, 0 is
 *   disallowed.
 * - ::cudaFuncAttributeClusterSchedulingPolicyPreference: The block
 *   scheduling policy of a function. The value type is cudaClusterSchedulingPolicy.
 *
 * \param func  - Function to get attributes of
 * \param attr  - Attribute to set
 * \param value - Value to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \ref ::cudaLaunchKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C++ API)",
 * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)",
 * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const void*) "cudaFuncGetAttributes (C API)",
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncSetAttribute(const void *func, enum cudaFuncAttribute attr, int value);

/**
 * \brief Returns the function name for a device entry function pointer.
 *
 * Returns in \p **name the function name associated with the symbol \p func .
 * The function name is returned as a null-terminated string. This API may
 * return a mangled name if the function is not declared as having C linkage.
 * If \p **name is NULL, ::cudaErrorInvalidValue is returned.
 * If \p func is not a device entry function, then it is assumed to
 * be a ::cudaKernel_t and used as is.
 *
 * \param name - The returned name of the function
 * \param func - The function pointer to retrieve name for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDeviceFunction
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \ref ::cudaFuncGetName(const char **name, const T *func) "cudaFuncGetName (C++ API)"
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetName(const char **name, const void *func);

/**
 * \brief Returns the offset and size of a kernel parameter in the device-side parameter layout.
 *
 * Queries the kernel parameter at \p paramIndex in \p func's list of parameters and returns
 * parameter information via \p paramOffset and \p paramSize. \p paramOffset returns the
 * offset of the parameter in the device-side parameter layout. \p paramSize returns the size
 * in bytes of the parameter. This information can be used to update kernel node parameters
 * from the device via ::cudaGraphKernelNodeSetParam() and ::cudaGraphKernelNodeUpdatesApply().
 * \p paramIndex must be less than the number of parameters that \p func takes.
 *
 * \param func        - The function to query
 * \param paramIndex  - The parameter index to query
 * \param paramOffset - The offset into the device-side parameter layout at which the parameter resides
 * \param paramSize   - The size of the parameter in the device-side parameter layout
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 * \note_cudaKernel_t
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetParamInfo(const void *func, size_t paramIndex, size_t *paramOffset, size_t *paramSize);

/**
 * \brief Returns the number of parameters used by the function
 *
 * Queries the number of kernel parameters used by \p func and returns it in \p paramCount.
 *
 * \param func        - The function to query
 * \param paramCount  - Returns the number of parameters used by the function
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 * \note_cudaKernel_t
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetParamCount(const void *func, size_t *paramCount);

/**
 * \brief Enqueues a host function call in a stream
 *
 * Enqueues a host function to run in a stream.  The function will be called
 * after currently enqueued work and will block work added after it.
 *
 * The host function must not make any CUDA API calls.  Attempting to use a
 * CUDA API may result in ::cudaErrorNotPermitted, but this is not required.
 * The host function must not perform any synchronization that may depend on
 * outstanding CUDA work not mandated to run earlier.  Host functions without a
 * mandated order (such as in independent streams) execute in undefined order
 * and may be serialized.
 *
 * For the purposes of Unified Memory, execution makes a number of guarantees:
 * <ul>
 *   <li>The stream is considered idle for the duration of the function's
 *   execution.  Thus, for example, the function may always use memory attached
 *   to the stream it was enqueued in.</li>
 *   <li>The start of execution of the function has the same effect as
 *   synchronizing an event recorded in the same stream immediately prior to
 *   the function.  It thus synchronizes streams which have been "joined"
 *   prior to the function.</li>
 *   <li>Adding device work to any stream does not have the effect of making
 *   the stream active until all preceding host functions and stream callbacks
 *   have executed.  Thus, for
 *   example, a function might use global attached memory even if work has
 *   been added to another stream, if the work has been ordered behind the
 *   function call with an event.</li>
 *   <li>Completion of the function does not cause a stream to become
 *   active except as described above.  The stream will remain idle
 *   if no device work follows the function, and will remain idle across
 *   consecutive host functions or stream callbacks without device work in
 *   between.  Thus, for example,
 *   stream synchronization can be done by signaling from a host function at the
 *   end of the stream.</li>
 * </ul>
 *
 * Note that, in constrast to ::cuStreamAddCallback, the function will not be
 * called in the event of an error in the CUDA context.
 *
 * \param hStream  - Stream to enqueue function call in
 * \param fn       - The function to call once preceding stream operations are complete
 * \param userData - User-specified data to be passed to the function
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate,
 * ::cudaStreamQuery,
 * ::cudaStreamSynchronize,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamDestroy,
 * ::cudaMallocManaged,
 * ::cudaStreamAttachMemAsync,
 * ::cudaStreamAddCallback,
 * ::cuLaunchHostFunc
 */
extern __host__ cudaError_t CUDARTAPI cudaLaunchHostFunc(cudaStream_t stream, cudaHostFn_t fn, void *userData);

/**
 * \brief Enqueues a host function call in a stream
 *
 * Enqueues a host function to run in a stream.  The function will be called
 * after currently enqueued work and will block work added after it.
 *
 * The host function must not make any CUDA API calls.  Attempting to use a
 * CUDA API may result in ::cudaErrorNotPermitted, but this is not required.
 * The host function must not perform any synchronization that may depend on
 * outstanding CUDA work not mandated to run earlier.  Host functions without a
 * mandated order (such as in independent streams) execute in undefined order
 * and may be serialized.
 *
 * For the purposes of Unified Memory, execution makes a number of guarantees:
 * <ul>
 *   <li>The stream is considered idle for the duration of the function's
 *   execution.  Thus, for example, the function may always use memory attached
 *   to the stream it was enqueued in.</li>
 *   <li>The start of execution of the function has the same effect as
 *   synchronizing an event recorded in the same stream immediately prior to
 *   the function.  It thus synchronizes streams which have been "joined"
 *   prior to the function.</li>
 *   <li>Adding device work to any stream does not have the effect of making
 *   the stream active until all preceding host functions and stream callbacks
 *   have executed.  Thus, for
 *   example, a function might use global attached memory even if work has
 *   been added to another stream, if the work has been ordered behind the
 *   function call with an event.</li>
 *   <li>Completion of the function does not cause a stream to become
 *   active except as described above.  The stream will remain idle
 *   if no device work follows the function, and will remain idle across
 *   consecutive host functions or stream callbacks without device work in
 *   between.  Thus, for example,
 *   stream synchronization can be done by signaling from a host function at the
 *   end of the stream.</li>
 * </ul>
 *
 * Note that, in constrast to ::cuStreamAddCallback, the function will not be
 * called in the event of an error in the CUDA context.
 *
 * \param hStream  - Stream to enqueue function call in
 * \param fn       - The function to call once preceding stream operations are complete
 * \param userData - User-specified data to be passed to the function
 * \param syncMode - Sync mode for the host function
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaStreamCreate,
 * ::cudaStreamQuery,
 * ::cudaStreamSynchronize,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamDestroy,
 * ::cudaMallocManaged,
 * ::cudaStreamAttachMemAsync,
 * ::cudaStreamAddCallback,
 * ::cuLaunchHostFunc
 */
extern __host__ cudaError_t CUDARTAPI cudaLaunchHostFunc_v2(cudaStream_t stream, cudaHostFn_t fn, void *userData, unsigned int syncMode);

/** @} */ /* END CUDART_EXECUTION */

/**
 * \defgroup CUDART_EXECUTION_DEPRECATED Execution Control [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated execution control functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the deprecated execution control functions of the CUDA runtime
 * application programming interface.
 *
 * Some functions have overloaded C++ API template versions documented separately in the
 * \ref CUDART_HIGHLEVEL "C++ API Routines" module.
 *
 * @{
 */

/**
 * \brief Sets the shared memory configuration for a device function
 *
 * \deprecated
 *
 * On devices with configurable shared memory banks, this function will 
 * force all subsequent launches of the specified device function to have
 * the given shared memory bank size configuration. On any given launch of the
 * function, the shared memory configuration of the device will be temporarily
 * changed if needed to suit the function's preferred configuration. Changes in
 * shared memory configuration between subsequent launches of functions, 
 * may introduce a device side synchronization point.
 *
 * Any per-function setting of shared memory bank size set via 
 * ::cudaFuncSetSharedMemConfig will override the device wide setting set by
 * ::cudaDeviceSetSharedMemConfig.
 *
 * Changing the shared memory bank size will not increase shared memory usage
 * or affect occupancy of kernels, but may have major effects on performance. 
 * Larger bank sizes will allow for greater potential bandwidth to shared memory,
 * but will change what kinds of accesses to shared memory will result in bank 
 * conflicts.
 *
 * This function will do nothing on devices with fixed shared memory bank size.
 *
 * For templated functions, pass the function symbol as follows:
 * func_name<template_arg_0,...,template_arg_N>
 *
 * The supported bank configurations are:
 * - ::cudaSharedMemBankSizeDefault: use the device's shared memory configuration
 *   when launching this function.
 * - ::cudaSharedMemBankSizeFourByte: set shared memory bank width to be 
 *   four bytes natively when launching this function.
 * - ::cudaSharedMemBankSizeEightByte: set shared memory bank width to be eight 
 *   bytes natively when launching this function.
 *
 * \param func   - Device function symbol
 * \param config - Requested shared memory configuration
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_string_api_deprecation2
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceSetSharedMemConfig,
 * ::cudaDeviceGetSharedMemConfig,
 * ::cudaDeviceSetCacheConfig,
 * ::cudaDeviceGetCacheConfig,
 * ::cudaFuncSetCacheConfig,
 * ::cuFuncSetSharedMemConfig
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaFuncSetSharedMemConfig(const void *func, enum cudaSharedMemConfig config);
/** @} */ /* END CUDART_EXECUTION_DEPRECATED */

/**
 * \defgroup CUDART_OCCUPANCY Occupancy
 *
 * ___MANBRIEF___ occupancy calculation functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the occupancy calculation functions of the CUDA runtime
 * application programming interface.
 *
 * Besides the occupancy calculator functions
 * (\ref ::cudaOccupancyMaxActiveBlocksPerMultiprocessor and \ref ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags),
 * there are also C++ only occupancy-based launch configuration functions documented in
 * \ref CUDART_HIGHLEVEL "C++ API Routines" module.
 *
 * See
 * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSize (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)"
 * \ref ::cudaOccupancyAvailableDynamicSMemPerBlock(size_t*, T, int, int) "cudaOccupancyAvailableDynamicSMemPerBlock (C++ API)",
 *
 * @{
 */

/**
 * \brief Returns occupancy for a device function
 *
 * Returns in \p *numBlocks the maximum number of active blocks per
 * streaming multiprocessor for the device function.
 *
 * \param numBlocks       - Returned occupancy
 * \param func            - Kernel function for which occupancy is calculated
 * \param blockSize       - Block size the kernel is intended to be launched with
 * \param dynamicSMemSize - Per-block dynamic shared memory usage intended, in bytes
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorUnknown,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags,
 * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeWithFlags (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags (C++ API)",
 * \ref ::cudaOccupancyAvailableDynamicSMemPerBlock(size_t*, T, int, int) "cudaOccupancyAvailableDynamicSMemPerBlock (C++ API)",
 * ::cuOccupancyMaxActiveBlocksPerMultiprocessor
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxActiveBlocksPerMultiprocessor(int *numBlocks, const void *func, int blockSize, size_t dynamicSMemSize);

/**
 * \brief Returns dynamic shared memory available per block when launching \p numBlocks blocks on SM.
 *
 * Returns in \p *dynamicSmemSize the maximum size of dynamic shared memory to allow \p numBlocks blocks per SM. 
 *
 * \param dynamicSmemSize - Returned maximum dynamic shared memory 
 * \param func            - Kernel function for which occupancy is calculated
 * \param numBlocks       - Number of blocks to fit on SM 
 * \param blockSize       - Size of the block
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorUnknown,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags,
 * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeWithFlags (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags (C++ API)",
 * ::cudaOccupancyAvailableDynamicSMemPerBlock
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyAvailableDynamicSMemPerBlock(size_t *dynamicSmemSize, const void *func, int numBlocks, int blockSize);

/**
 * \brief Returns occupancy for a device function with the specified flags
 *
 * Returns in \p *numBlocks the maximum number of active blocks per
 * streaming multiprocessor for the device function.
 *
 * The \p flags parameter controls how special cases are handled. Valid flags include:
 *
 * - ::cudaOccupancyDefault: keeps the default behavior as
 *   ::cudaOccupancyMaxActiveBlocksPerMultiprocessor
 *
 * - ::cudaOccupancyDisableCachingOverride: This flag suppresses the default behavior
 *   on platform where global caching affects occupancy. On such platforms, if caching
 *   is enabled, but per-block SM resource usage would result in zero occupancy, the
 *   occupancy calculator will calculate the occupancy as if caching is disabled.
 *   Setting this flag makes the occupancy calculator to return 0 in such cases.
 *   More information can be found about this feature in the "Unified L1/Texture Cache"
 *   section of the Maxwell tuning guide.
 *
 * \param numBlocks       - Returned occupancy
 * \param func            - Kernel function for which occupancy is calculated
 * \param blockSize       - Block size the kernel is intended to be launched with
 * \param dynamicSMemSize - Per-block dynamic shared memory usage intended, in bytes
 * \param flags           - Requested behavior for the occupancy calculator
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorUnknown,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa ::cudaOccupancyMaxActiveBlocksPerMultiprocessor,
 * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeWithFlags (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)",
 * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags (C++ API)",
 * \ref ::cudaOccupancyAvailableDynamicSMemPerBlock(size_t*, T, int, int) "cudaOccupancyAvailableDynamicSMemPerBlock (C++ API)",
 * ::cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags(int *numBlocks, const void *func, int blockSize, size_t dynamicSMemSize, unsigned int flags);

/**
 * \brief Given the kernel function (\p func) and launch configuration
 * (\p config), return the maximum cluster size in \p *clusterSize.
 *
 * The cluster dimensions in \p config are ignored. If func has a required
 * cluster size set (see ::cudaFuncGetAttributes),\p *clusterSize will reflect 
 * the required cluster size.
 *
 * By default this function will always return a value that's portable on
 * future hardware. A higher value may be returned if the kernel function
 * allows non-portable cluster sizes.
 *
 * This function will respect the compile time launch bounds.
 *
 * \param clusterSize - Returned maximum cluster size that can be launched
 *                      for the given kernel function and launch configuration
 * \param func        - Kernel function for which maximum cluster
 *                      size is calculated
 * \param config      - Launch configuration for the given kernel function
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorUnknown,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa ::cudaFuncGetAttributes
 * \ref ::cudaOccupancyMaxPotentialClusterSize(int*, T, const cudaLaunchConfig_t*) "cudaOccupancyMaxPotentialClusterSize (C++ API)",
 * ::cuOccupancyMaxPotentialClusterSize
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxPotentialClusterSize(int *clusterSize, const void *func, const cudaLaunchConfig_t *launchConfig);


/**
 * \brief Given the kernel function (\p func) and launch configuration
 * (\p config), return the maximum number of clusters that could co-exist
 * on the target device in \p *numClusters.
 *
 * If the function has required cluster size already set (see
 * ::cudaFuncGetAttributes), the cluster size from config must either be
 * unspecified or match the required size.
 * Without required sizes, the cluster size must be specified in config,
 * else the function will return an error.
 *
 * Note that various attributes of the kernel function may affect occupancy
 * calculation. Runtime environment may affect how the hardware schedules
 * the clusters, so the calculated occupancy is not guaranteed to be achievable.
 *
 * \param numClusters - Returned maximum number of clusters that
 *                      could co-exist on the target device
 * \param func        - Kernel function for which maximum number
 *                      of clusters are calculated
 * \param config      - Launch configuration for the given kernel function
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidClusterSize,
 * ::cudaErrorUnknown,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * ::cudaFuncGetAttributes
 * \ref ::cudaOccupancyMaxActiveClusters(int*, T, const cudaLaunchConfig_t*) "cudaOccupancyMaxActiveClusters (C++ API)",
 * ::cuOccupancyMaxActiveClusters
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxActiveClusters(int *numClusters, const void *func, const cudaLaunchConfig_t *launchConfig);
/** @} */ /* END CUDA_OCCUPANCY */

/**
 * \defgroup CUDART_MEMORY Memory Management
 *
 * ___MANBRIEF___ memory management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the memory management functions of the CUDA runtime
 * application programming interface.
 *
 * Some functions have overloaded C++ API template versions documented separately in the
 * \ref CUDART_HIGHLEVEL "C++ API Routines" module.
 *
 * @{
 */

/**
 * \brief Allocates memory that will be automatically managed by the Unified Memory system
 *
 * Allocates \p size bytes of managed memory on the device and returns in
 * \p *devPtr a pointer to the allocated memory. If the device doesn't support
 * allocating managed memory, ::cudaErrorNotSupported is returned. Support
 * for managed memory can be queried using the device attribute
 * ::cudaDevAttrManagedMemory. The allocated memory is suitably
 * aligned for any kind of variable. The memory is not cleared. If \p size
 * is 0, ::cudaMallocManaged returns ::cudaErrorInvalidValue. The pointer
 * is valid on the CPU and on all GPUs in the system that support managed memory.
 * All accesses to this pointer must obey the Unified Memory programming model.
 *
 * \p flags specifies the default stream association for this allocation.
 * \p flags must be one of ::cudaMemAttachGlobal or ::cudaMemAttachHost. The
 * default value for \p flags is ::cudaMemAttachGlobal.
 * If ::cudaMemAttachGlobal is specified, then this memory is accessible from
 * any stream on any device. If ::cudaMemAttachHost is specified, then the
 * allocation should not be accessed from devices that have a zero value for the
 * device attribute ::cudaDevAttrConcurrentManagedAccess; an explicit call to
 * ::cudaStreamAttachMemAsync will be required to enable access on such devices.
 *
 * If the association is later changed via ::cudaStreamAttachMemAsync to
 * a single stream, the default association, as specifed during ::cudaMallocManaged,
 * is restored when that stream is destroyed. For __managed__ variables, the
 * default association is always ::cudaMemAttachGlobal. Note that destroying a
 * stream is an asynchronous operation, and as a result, the change to default
 * association won't happen until all work in the stream has completed.
 *
 * Memory allocated with ::cudaMallocManaged should be released with ::cudaFree.
 *
 * Device memory oversubscription is possible for GPUs that have a non-zero value for the
 * device attribute ::cudaDevAttrConcurrentManagedAccess. Managed memory on
 * such GPUs may be evicted from device memory to host memory at any time by the Unified
 * Memory driver in order to make room for other allocations.
 *
 * In a system where all GPUs have a non-zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess, managed memory may not be populated when this
 * API returns and instead may be populated on access. In such systems, managed memory can
 * migrate to any processor's memory at any time. The Unified Memory driver will employ heuristics to
 * maintain data locality and prevent excessive page faults to the extent possible. The application
 * can also guide the driver about memory usage patterns via ::cudaMemAdvise. The application
 * can also explicitly migrate memory to a desired processor's memory via
 * ::cudaMemPrefetchAsync.
 *
 * In a multi-GPU system where all of the GPUs have a zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess and all the GPUs have peer-to-peer support
 * with each other, the physical storage for managed memory is created on the GPU which is active
 * at the time ::cudaMallocManaged is called. All other GPUs will reference the data at reduced
 * bandwidth via peer mappings over the PCIe bus. The Unified Memory driver does not migrate
 * memory among such GPUs.
 *
 * In a multi-GPU system where not all GPUs have peer-to-peer support with each other and
 * where the value of the device attribute ::cudaDevAttrConcurrentManagedAccess
 * is zero for at least one of those GPUs, the location chosen for physical storage of managed
 * memory is system-dependent.
 * - On Linux, the location chosen will be device memory as long as the current set of active
 * contexts are on devices that either have peer-to-peer support with each other or have a
 * non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess.
 * If there is an active context on a GPU that does not have a non-zero value for that device
 * attribute and it does not have peer-to-peer support with the other devices that have active
 * contexts on them, then the location for physical storage will be 'zero-copy' or host memory.
 * Note that this means that managed memory that is located in device memory is migrated to
 * host memory if a new context is created on a GPU that doesn't have a non-zero value for
 * the device attribute and does not support peer-to-peer with at least one of the other devices
 * that has an active context. This in turn implies that context creation may fail if there is
 * insufficient host memory to migrate all managed allocations.
 * - On Windows, the physical storage is always created in 'zero-copy' or host memory.
 * All GPUs will reference the data at reduced bandwidth over the PCIe bus. In these
 * circumstances, use of the environment variable CUDA_VISIBLE_DEVICES is recommended to
 * restrict CUDA to only use those GPUs that have peer-to-peer support.
 * Alternatively, users can also set CUDA_MANAGED_FORCE_DEVICE_ALLOC to a non-zero
 * value to force the driver to always use device memory for physical storage.
 * When this environment variable is set to a non-zero value, all devices used in
 * that process that support managed memory have to be peer-to-peer compatible
 * with each other. The error ::cudaErrorInvalidDevice will be returned if a device
 * that supports managed memory is used and it is not peer-to-peer compatible with
 * any of the other managed memory supporting devices that were previously used in
 * that process, even if ::cudaDeviceReset has been called on those devices. These
 * environment variables are described in the CUDA programming guide under the
 * "CUDA environment variables" section.
 *
 * \param devPtr - Pointer to allocated device memory
 * \param size   - Requested allocation size in bytes
 * \param flags  - Must be either ::cudaMemAttachGlobal or ::cudaMemAttachHost (defaults to ::cudaMemAttachGlobal)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, ::cudaFreeArray,
 * ::cudaMalloc3D, ::cudaMalloc3DArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc, ::cudaDeviceGetAttribute, ::cudaStreamAttachMemAsync,
 * ::cuMemAllocManaged
 */
#if defined(__cplusplus)
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMallocManaged(void **devPtr, size_t size, unsigned int flags = cudaMemAttachGlobal);
#else
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMallocManaged(void **devPtr, size_t size, unsigned int flags);
#endif

/**
 * \brief Allocate memory on the device
 *
 * Allocates \p size bytes of linear memory on the device and returns in
 * \p *devPtr a pointer to the allocated memory. The allocated memory is
 * suitably aligned for any kind of variable. The memory is not cleared.
 * ::cudaMalloc() returns ::cudaErrorMemoryAllocation in case of failure.
 *
 * The device version of ::cudaFree cannot be used with a \p *devPtr
 * allocated using the host API, and vice versa.
 *
 * \param devPtr - Pointer to allocated device memory
 * \param size   - Requested allocation size in bytes
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, ::cudaFreeArray,
 * ::cudaMalloc3D, ::cudaMalloc3DArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::cuMemAlloc
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMalloc(void **devPtr, size_t size);

/**
 * \brief Allocates page-locked memory on the host
 *
 * Allocates \p size bytes of host memory that is page-locked and accessible
 * to the device. The driver tracks the virtual memory ranges allocated with
 * this function and automatically accelerates calls to functions such as
 * ::cudaMemcpy*(). Since the memory can be accessed directly by the device,
 * it can be read or written with much higher bandwidth than pageable memory
 * obtained with functions such as ::malloc(). 

 * On systems where ::pageableMemoryAccessUsesHostPageTables
 * is true, ::cudaMallocHost may not page-lock the allocated memory.

 * Page-locking excessive amounts of memory with ::cudaMallocHost() may degrade 
 * system performance, since it reduces the amount of memory available to the 
 * system for paging. As a result, this function is best used sparingly to allocate 
 * staging areas for data exchange between host and device.
 *
 * \param ptr  - Pointer to allocated host memory
 * \param size - Requested allocation size in bytes
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaMallocArray, ::cudaMalloc3D,
 * ::cudaMalloc3DArray, ::cudaHostAlloc, ::cudaFree, ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t, unsigned int) "cudaMallocHost (C++ API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::cuMemAllocHost
 */
extern __host__ cudaError_t CUDARTAPI cudaMallocHost(void **ptr, size_t size);

/**
 * \brief Allocates pitched memory on the device
 *
 * Allocates at least \p width (in bytes) * \p height bytes of linear memory
 * on the device and returns in \p *devPtr a pointer to the allocated memory.
 * The function may pad the allocation to ensure that corresponding pointers
 * in any given row will continue to meet the alignment requirements for
 * coalescing as the address is updated from row to row. The pitch returned in
 * \p *pitch by ::cudaMallocPitch() is the width in bytes of the allocation.
 * The intended usage of \p pitch is as a separate parameter of the allocation,
 * used to compute addresses within the 2D array. Given the row and column of
 * an array element of type \p T, the address is computed as:
 * \code
    T* pElement = (T*)((char*)BaseAddress + Row * pitch) + Column;
   \endcode
 *
 * For allocations of 2D arrays, it is recommended that programmers consider
 * performing pitch allocations using ::cudaMallocPitch(). Due to pitch
 * alignment restrictions in the hardware, this is especially true if the
 * application will be performing 2D memory copies between different regions
 * of device memory (whether linear memory or CUDA arrays).
 *
 * \param devPtr - Pointer to allocated pitched device memory
 * \param pitch  - Pitch for allocation
 * \param width  - Requested pitched allocation width (in bytes)
 * \param height - Requested pitched allocation height
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaFree, ::cudaMallocArray, ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaMalloc3D, ::cudaMalloc3DArray,
 * ::cudaHostAlloc,
 * ::cuMemAllocPitch
 */
extern __host__ cudaError_t CUDARTAPI cudaMallocPitch(void **devPtr, size_t *pitch, size_t width, size_t height);

/**
 * \brief Allocate an array on the device
 *
 * Allocates a CUDA array according to the ::cudaChannelFormatDesc structure
 * \p desc and returns a handle to the new CUDA array in \p *array.
 *
 * The ::cudaChannelFormatDesc is defined as:
 * \code
    struct cudaChannelFormatDesc {
        int x, y, z, w;
    enum cudaChannelFormatKind f;
    };
    \endcode
 * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned,
 * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat.
 *
 * The \p flags parameter enables different options to be specified that affect
 * the allocation, as follows.
 * - ::cudaArrayDefault: This flag's value is defined to be 0 and provides default array allocation
 * - ::cudaArraySurfaceLoadStore: Allocates an array that can be read from or written to using a surface reference
 * - ::cudaArrayTextureGather: This flag indicates that texture gather operations will be performed on the array.
 * - ::cudaArraySparse: Allocates a CUDA array without physical backing memory. The subregions within this sparse array
 *   can later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. 
 *   The physical backing memory must be allocated via ::cuMemCreate.
 * - ::cudaArrayDeferredMapping: Allocates a CUDA array without physical backing memory. The entire array can 
 *   later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. 
 *   The physical backing memory must be allocated via ::cuMemCreate.
 *
 * \p width and \p height must meet certain size requirements. See ::cudaMalloc3DArray() for more details.
 *
 * \param array  - Pointer to allocated array in device memory
 * \param desc   - Requested channel format
 * \param width  - Requested array allocation width
 * \param height - Requested array allocation height
 * \param flags  - Requested properties of allocated array
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaMalloc3D, ::cudaMalloc3DArray,
 * ::cudaHostAlloc,
 * ::cuArrayCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaMallocArray(cudaArray_t *array, const struct cudaChannelFormatDesc *desc, size_t width, size_t height __dv(0), unsigned int flags __dv(0));

/**
 * \brief Frees memory on the device
 *
 * Frees the memory space pointed to by \p devPtr, which must have been
 * returned by a previous call to one of the following memory allocation APIs -
 * ::cudaMalloc(), ::cudaMallocPitch(), ::cudaMallocManaged(), ::cudaMallocAsync(),
 * ::cudaMallocFromPoolAsync().
 * 
 * Note - This API will not perform any implicit synchronization when the pointer was
 * allocated with ::cudaMallocAsync or ::cudaMallocFromPoolAsync. Callers must ensure
 * that all accesses to these pointer have completed before invoking ::cudaFree. For
 * best performance and memory reuse, users should use ::cudaFreeAsync to free memory
 * allocated via the stream ordered memory allocator.
 * For all other pointers, this API may perform implicit synchronization.
 * 
 * If ::cudaFree(\p devPtr) has already been called before,
 * an error is returned. If \p devPtr is 0, no operation is performed.
 * ::cudaFree() returns ::cudaErrorValue in case of failure.
 *
 * The device version of ::cudaFree cannot be used with a \p *devPtr
 * allocated using the host API, and vice versa.
 *
 * \param devPtr - Device pointer to memory to free
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaMallocManaged, ::cudaMallocArray, ::cudaFreeArray, ::cudaMallocAsync, ::cudaMallocFromPoolAsync
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaFreeAsync
 * ::cudaHostAlloc,
 * ::cuMemFree
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFree(void *devPtr);

/**
 * \brief Frees page-locked memory
 *
 * Frees the memory space pointed to by \p hostPtr, which must have been
 * returned by a previous call to ::cudaMallocHost() or ::cudaHostAlloc().
 *
 * \param ptr - Pointer to memory to free
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray,
 * ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaHostAlloc,
 * ::cuMemFreeHost
 */
extern __host__ cudaError_t CUDARTAPI cudaFreeHost(void *ptr);

/**
 * \brief Frees an array on the device
 *
 * Frees the CUDA array \p array, which must have been returned by a
 * previous call to ::cudaMallocArray(). If \p devPtr is 0,
 * no operation is performed.
 *
 * \param array - Pointer to array to free
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::cuArrayDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaFreeArray(cudaArray_t array);

/**
 * \brief Frees a mipmapped array on the device
 *
 * Frees the CUDA mipmapped array \p mipmappedArray, which must have been 
 * returned by a previous call to ::cudaMallocMipmappedArray(). If \p devPtr
 * is 0, no operation is performed.
 *
 * \param mipmappedArray - Pointer to mipmapped array to free
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::cuMipmappedArrayDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaFreeMipmappedArray(cudaMipmappedArray_t mipmappedArray);


/**
 * \brief Allocates page-locked memory on the host
 *
 * Allocates \p size bytes of host memory that is page-locked and accessible
 * to the device. The driver tracks the virtual memory ranges allocated with
 * this function and automatically accelerates calls to functions such as
 * ::cudaMemcpy(). Since the memory can be accessed directly by the device, it
 * can be read or written with much higher bandwidth than pageable memory
 * obtained with functions such as ::malloc(). Allocating excessive amounts of
 * pinned memory may degrade system performance, since it reduces the amount
 * of memory available to the system for paging. As a result, this function is
 * best used sparingly to allocate staging areas for data exchange between host
 * and device.
 *
 * The \p flags parameter enables different options to be specified that affect
 * the allocation, as follows.
 * - ::cudaHostAllocDefault: This flag's value is defined to be 0 and causes
 * ::cudaHostAlloc() to emulate ::cudaMallocHost().
 * - ::cudaHostAllocPortable: The memory returned by this call will be
 * considered as pinned memory by all CUDA contexts, not just the one that
 * performed the allocation.
 * - ::cudaHostAllocMapped: Maps the allocation into the CUDA address space.
 * The device pointer to the memory may be obtained by calling
 * ::cudaHostGetDevicePointer().
 * - ::cudaHostAllocWriteCombined: Allocates the memory as write-combined (WC).
 * WC memory can be transferred across the PCI Express bus more quickly on some
 * system configurations, but cannot be read efficiently by most CPUs.  WC
 * memory is a good option for buffers that will be written by the CPU and read
 * by the device via mapped pinned memory or host->device transfers.
 *
 * All of these flags are orthogonal to one another: a developer may allocate
 * memory that is portable, mapped and/or write-combined with no restrictions.
 *
 * In order for the ::cudaHostAllocMapped flag to have any effect, the CUDA context
 * must support the ::cudaDeviceMapHost flag, which can be checked via
 * ::cudaGetDeviceFlags(). The ::cudaDeviceMapHost flag is implicitly set for
 * contexts created via the runtime API.
 *
 * The ::cudaHostAllocMapped flag may be specified on CUDA contexts for devices
 * that do not support mapped pinned memory. The failure is deferred to
 * ::cudaHostGetDevicePointer() because the memory may be mapped into other
 * CUDA contexts via the ::cudaHostAllocPortable flag.
 *
 * Memory allocated by this function must be freed with ::cudaFreeHost().
 *
 * \param pHost - Device pointer to allocated memory
 * \param size  - Requested allocation size in bytes
 * \param flags - Requested properties of allocated memory
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaSetDeviceFlags,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost,
 * ::cudaGetDeviceFlags,
 * ::cuMemHostAlloc
 */
extern __host__ cudaError_t CUDARTAPI cudaHostAlloc(void **pHost, size_t size, unsigned int flags);

/**
 * \brief Registers an existing host memory range for use by CUDA
 *
 * Page-locks the memory range specified by \p ptr and \p size and maps it
 * for the device(s) as specified by \p flags. This memory range also is added
 * to the same tracking mechanism as ::cudaHostAlloc() to automatically accelerate
 * calls to functions such as ::cudaMemcpy(). Since the memory can be accessed 
 * directly by the device, it can be read or written with much higher bandwidth 
 * than pageable memory that has not been registered.  Page-locking excessive
 * amounts of memory may degrade system performance, since it reduces the amount
 * of memory available to the system for paging. As a result, this function is
 * best used sparingly to register staging areas for data exchange between
 * host and device.
 * 
 * On systems where ::pageableMemoryAccessUsesHostPageTables is true, ::cudaHostRegister 
 * will not page-lock the memory range specified by \p ptr but only populate 
 * unpopulated pages.
 *
 * ::cudaHostRegister is supported only on I/O coherent devices that have a non-zero
 * value for the device attribute ::cudaDevAttrHostRegisterSupported.
 *
 * The \p flags parameter enables different options to be specified that
 * affect the allocation, as follows.
 *
 * - ::cudaHostRegisterDefault: On a system with unified virtual addressing,
 *   the memory will be both mapped and portable.  On a system with no unified
 *   virtual addressing, the memory will be neither mapped nor portable.
 *
 * - ::cudaHostRegisterPortable: The memory returned by this call will be
 *   considered as pinned memory by all CUDA contexts, not just the one that
 *   performed the allocation.
 *
 * - ::cudaHostRegisterMapped: Maps the allocation into the CUDA address
 *   space. The device pointer to the memory may be obtained by calling
 *   ::cudaHostGetDevicePointer().
 *
 * - ::cudaHostRegisterIoMemory: The passed memory pointer is treated as
 *   pointing to some memory-mapped I/O space, e.g. belonging to a
 *   third-party PCIe device, and it will marked as non cache-coherent and
 *   contiguous.
 *
 * - ::cudaHostRegisterReadOnly: The passed memory pointer is treated as
 *   pointing to memory that is considered read-only by the device.  On
 *   platforms without ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, this
 *   flag is required in order to register memory mapped to the CPU as
 *   read-only.  Support for the use of this flag can be queried from the device
 *   attribute ::cudaDevAttrHostRegisterReadOnlySupported.  Using this flag with
 *   a current context associated with a device that does not have this attribute
 *   set will cause ::cudaHostRegister to error with cudaErrorNotSupported.
 *
 * All of these flags are orthogonal to one another: a developer may page-lock
 * memory that is portable or mapped with no restrictions.
 *
 * The CUDA context must have been created with the ::cudaMapHost flag in
 * order for the ::cudaHostRegisterMapped flag to have any effect.
 *
 * The ::cudaHostRegisterMapped flag may be specified on CUDA contexts for
 * devices that do not support mapped pinned memory. The failure is deferred
 * to ::cudaHostGetDevicePointer() because the memory may be mapped into
 * other CUDA contexts via the ::cudaHostRegisterPortable flag.
 *
 * For devices that have a non-zero value for the device attribute
 * ::cudaDevAttrCanUseHostPointerForRegisteredMem, the memory
 * can also be accessed from the device using the host pointer \p ptr.
 * The device pointer returned by ::cudaHostGetDevicePointer() may or may not
 * match the original host pointer \p ptr and depends on the devices visible to the
 * application. If all devices visible to the application have a non-zero value for the
 * device attribute, the device pointer returned by ::cudaHostGetDevicePointer()
 * will match the original pointer \p ptr. If any device visible to the application
 * has a zero value for the device attribute, the device pointer returned by
 * ::cudaHostGetDevicePointer() will not match the original host pointer \p ptr,
 * but it will be suitable for use on all devices provided Unified Virtual Addressing
 * is enabled. In such systems, it is valid to access the memory using either pointer
 * on devices that have a non-zero value for the device attribute. Note however that
 * such devices should access the memory using only of the two pointers and not both.
 *
 * The memory page-locked by this function must be unregistered with ::cudaHostUnregister().
 *
 * \param ptr   - Host pointer to memory to page-lock
 * \param size  - Size in bytes of the address range to page-lock in bytes
 * \param flags - Flags for allocation request
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorHostMemoryAlreadyRegistered,
 * ::cudaErrorNotSupported,
 * ::cudaErrorExternalDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaHostUnregister, ::cudaHostGetFlags, ::cudaHostGetDevicePointer,
 * ::cuMemHostRegister
 */
extern __host__ cudaError_t CUDARTAPI cudaHostRegister(void *ptr, size_t size, unsigned int flags);

/**
 * \brief Unregisters a memory range that was registered with cudaHostRegister
 *
 * Unmaps the memory range whose base address is specified by \p ptr, and makes
 * it pageable again.
 *
 * The base address must be the same one specified to ::cudaHostRegister().
 *
 * \param ptr - Host pointer to memory to unregister
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorHostMemoryNotRegistered
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaHostUnregister,
 * ::cuMemHostUnregister
 */
extern __host__ cudaError_t CUDARTAPI cudaHostUnregister(void *ptr);

/**
 * \brief Passes back device pointer of mapped host memory allocated by
 * cudaHostAlloc or registered by cudaHostRegister
 *
 * Passes back the device pointer corresponding to the mapped, pinned host
 * buffer allocated by ::cudaHostAlloc() or registered by ::cudaHostRegister().
 *
 * ::cudaHostGetDevicePointer() will fail if the ::cudaDeviceMapHost flag was
 * not specified before deferred context creation occurred, or if called on a
 * device that does not support mapped, pinned memory.
 *
 * For devices that have a non-zero value for the device attribute
 * ::cudaDevAttrCanUseHostPointerForRegisteredMem, the memory
 * can also be accessed from the device using the host pointer \p pHost.
 * The device pointer returned by ::cudaHostGetDevicePointer() may or may not
 * match the original host pointer \p pHost and depends on the devices visible to the
 * application. If all devices visible to the application have a non-zero value for the
 * device attribute, the device pointer returned by ::cudaHostGetDevicePointer()
 * will match the original pointer \p pHost. If any device visible to the application
 * has a zero value for the device attribute, the device pointer returned by
 * ::cudaHostGetDevicePointer() will not match the original host pointer \p pHost,
 * but it will be suitable for use on all devices provided Unified Virtual Addressing
 * is enabled. In such systems, it is valid to access the memory using either pointer
 * on devices that have a non-zero value for the device attribute. Note however that
 * such devices should access the memory using only of the two pointers and not both.
 *
 * \p flags provides for future releases.  For now, it must be set to 0.
 *
 * \param pDevice - Returned device pointer for mapped memory
 * \param pHost   - Requested host pointer mapping
 * \param flags   - Flags for extensions (must be 0 for now)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaSetDeviceFlags, ::cudaHostAlloc,
 * ::cuMemHostGetDevicePointer
 */
extern __host__ cudaError_t CUDARTAPI cudaHostGetDevicePointer(void **pDevice, void *pHost, unsigned int flags);

/**
 * \brief Passes back flags used to allocate pinned host memory allocated by
 * cudaHostAlloc
 *
 * ::cudaHostGetFlags() will fail if the input pointer does not
 * reside in an address range allocated by ::cudaHostAlloc().
 *
 * \param pFlags - Returned flags word
 * \param pHost - Host pointer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaHostAlloc,
 * ::cuMemHostGetFlags
 */
extern __host__ cudaError_t CUDARTAPI cudaHostGetFlags(unsigned int *pFlags, void *pHost);

/**
 * \brief Allocates logical 1D, 2D, or 3D memory objects on the device
 *
 * Allocates at least \p width * \p height * \p depth bytes of linear memory
 * on the device and returns a ::cudaPitchedPtr in which \p ptr is a pointer
 * to the allocated memory. The function may pad the allocation to ensure
 * hardware alignment requirements are met. The pitch returned in the \p pitch
 * field of \p pitchedDevPtr is the width in bytes of the allocation.
 *
 * The returned ::cudaPitchedPtr contains additional fields \p xsize and
 * \p ysize, the logical width and height of the allocation, which are
 * equivalent to the \p width and \p height \p extent parameters provided by
 * the programmer during allocation.
 *
 * For allocations of 2D and 3D objects, it is highly recommended that
 * programmers perform allocations using ::cudaMalloc3D() or
 * ::cudaMallocPitch(). Due to alignment restrictions in the hardware, this is
 * especially true if the application will be performing memory copies
 * involving 2D or 3D objects (whether linear memory or CUDA arrays).
 *
 * \param pitchedDevPtr  - Pointer to allocated pitched device memory
 * \param extent         - Requested allocation size (\p width field in bytes)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMallocPitch, ::cudaFree, ::cudaMemcpy3D, ::cudaMemset3D,
 * ::cudaMalloc3DArray, ::cudaMallocArray, ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc, ::make_cudaPitchedPtr, ::make_cudaExtent,
 * ::cuMemAllocPitch
 */
extern __host__ cudaError_t CUDARTAPI cudaMalloc3D(struct cudaPitchedPtr* pitchedDevPtr, struct cudaExtent extent);

/**
 * \brief Allocate an array on the device
 *
 * Allocates a CUDA array according to the ::cudaChannelFormatDesc structure
 * \p desc and returns a handle to the new CUDA array in \p *array.
 *
 * The ::cudaChannelFormatDesc is defined as:
 * \code
    struct cudaChannelFormatDesc {
        int x, y, z, w;
        enum cudaChannelFormatKind f;
    };
    \endcode
 * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned,
 * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat.
 *
 * ::cudaMalloc3DArray() can allocate the following:
 *
 * - A 1D array is allocated if the height and depth extents are both zero.
 * - A 2D array is allocated if only the depth extent is zero.
 * - A 3D array is allocated if all three extents are non-zero.
 * - A 1D layered CUDA array is allocated if only the height extent is zero and
 * the cudaArrayLayered flag is set. Each layer is a 1D array. The number of layers is 
 * determined by the depth extent.
 * - A 2D layered CUDA array is allocated if all three extents are non-zero and 
 * the cudaArrayLayered flag is set. Each layer is a 2D array. The number of layers is 
 * determined by the depth extent.
 * - A cubemap CUDA array is allocated if all three extents are non-zero and the
 * cudaArrayCubemap flag is set. Width must be equal to height, and depth must be six. A cubemap is
 * a special type of 2D layered CUDA array, where the six layers represent the six faces of a cube. 
 * The order of the six layers in memory is the same as that listed in ::cudaGraphicsCubeFace.
 * - A cubemap layered CUDA array is allocated if all three extents are non-zero, and both,
 * cudaArrayCubemap and cudaArrayLayered flags are set. Width must be equal to height, and depth must be 
 * a multiple of six. A cubemap layered CUDA array is a special type of 2D layered CUDA array that consists 
 * of a collection of cubemaps. The first six layers represent the first cubemap, the next six layers form 
 * the second cubemap, and so on.
 *
 *
 * The \p flags parameter enables different options to be specified that affect
 * the allocation, as follows.
 * - ::cudaArrayDefault: This flag's value is defined to be 0 and provides default array allocation
 * - ::cudaArrayLayered: Allocates a layered CUDA array, with the depth extent indicating the number of layers
 * - ::cudaArrayCubemap: Allocates a cubemap CUDA array. Width must be equal to height, and depth must be six.
 *   If the cudaArrayLayered flag is also set, depth must be a multiple of six.
 * - ::cudaArraySurfaceLoadStore: Allocates a CUDA array that could be read from or written to using a surface
 *   reference.
 * - ::cudaArrayTextureGather: This flag indicates that texture gather operations will be performed on the CUDA 
 *   array. Texture gather can only be performed on 2D CUDA arrays.
 * - ::cudaArraySparse: Allocates a CUDA array without physical backing memory. The subregions within this sparse array 
 *   can later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. This flag can only be used for 
 *   creating 2D, 3D or 2D layered sparse CUDA arrays. The physical backing memory must be allocated via ::cuMemCreate.
 * - ::cudaArrayDeferredMapping: Allocates a CUDA array without physical backing memory. The entire array can
 *   later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. The physical backing memory must be allocated
 *   via ::cuMemCreate.
 *
 * The width, height and depth extents must meet certain size requirements as listed in the following table.
 * All values are specified in elements.
 *
 * Note that 2D CUDA arrays have different size requirements if the ::cudaArrayTextureGather flag is set. In that
 * case, the valid range for (width, height, depth) is ((1,maxTexture2DGather[0]), (1,maxTexture2DGather[1]), 0).
 *
 * \xmlonly
 * <table outputclass="xmlonly">
 * <tgroup cols="3" colsep="1" rowsep="1">
 * <colspec colname="c1" colwidth="1.0*"/>
 * <colspec colname="c2" colwidth="3.0*"/>
 * <colspec colname="c3" colwidth="3.0*"/>
 * <thead>
 * <row>
 * <entry>CUDA array type</entry>
 * <entry>Valid extents that must always be met {(width range in elements),
 * (height range), (depth range)}</entry>
 * <entry>Valid extents with cudaArraySurfaceLoadStore set {(width range in
 * elements), (height range), (depth range)}</entry>
 * </row>
 * </thead>
 * <tbody>
 * <row>
 * <entry>1D</entry>
 * <entry>{ (1,maxTexture1D), 0, 0 }</entry>
 * <entry>{ (1,maxSurface1D), 0, 0 }</entry>
 * </row>
 * <row>
 * <entry>2D</entry>
 * <entry>{ (1,maxTexture2D[0]), (1,maxTexture2D[1]), 0 }</entry>
 * <entry>{ (1,maxSurface2D[0]), (1,maxSurface2D[1]), 0 }</entry>
 * </row>
 * <row>
 * <entry>3D</entry>
 * <entry>{ (1,maxTexture3D[0]), (1,maxTexture3D[1]), (1,maxTexture3D[2]) }
 * OR { (1,maxTexture3DAlt[0]), (1,maxTexture3DAlt[1]),
 * (1,maxTexture3DAlt[2]) }</entry>
 * <entry>{ (1,maxSurface3D[0]), (1,maxSurface3D[1]), (1,maxSurface3D[2]) }</entry>
 * </row>
 * <row>
 * <entry>1D Layered</entry>
 * <entry>{ (1,maxTexture1DLayered[0]), 0, (1,maxTexture1DLayered[1]) }</entry>
 * <entry>{ (1,maxSurface1DLayered[0]), 0, (1,maxSurface1DLayered[1]) }</entry>
 * </row>
 * <row>
 * <entry>2D Layered</entry>
 * <entry>{ (1,maxTexture2DLayered[0]), (1,maxTexture2DLayered[1]),
 * (1,maxTexture2DLayered[2]) }</entry>
 * <entry>{ (1,maxSurface2DLayered[0]), (1,maxSurface2DLayered[1]),
 * (1,maxSurface2DLayered[2]) }</entry>
 * </row>
 * <row>
 * <entry>Cubemap</entry>
 * <entry>{ (1,maxTextureCubemap), (1,maxTextureCubemap), 6 }</entry>
 * <entry>{ (1,maxSurfaceCubemap), (1,maxSurfaceCubemap), 6 }</entry>
 * </row>
 * <row>
 * <entry>Cubemap Layered</entry>
 * <entry>{ (1,maxTextureCubemapLayered[0]), (1,maxTextureCubemapLayered[0]),
 * (1,maxTextureCubemapLayered[1]) }</entry>
 * <entry>{ (1,maxSurfaceCubemapLayered[0]), (1,maxSurfaceCubemapLayered[0]),
 * (1,maxSurfaceCubemapLayered[1]) }</entry>
 * </row>
 * </tbody>
 * </tgroup>
 * </table>
 * \endxmlonly
 *
 * \param array  - Pointer to allocated array in device memory
 * \param desc   - Requested channel format
 * \param extent - Requested allocation size (\p width field in elements)
 * \param flags  - Flags for extensions
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc3D, ::cudaMalloc, ::cudaMallocPitch, ::cudaFree,
 * ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::make_cudaExtent,
 * ::cuArray3DCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaMalloc3DArray(cudaArray_t *array, const struct cudaChannelFormatDesc* desc, struct cudaExtent extent, unsigned int flags __dv(0));

/**
 * \brief Allocate a mipmapped array on the device
 *
 * Allocates a CUDA mipmapped array according to the ::cudaChannelFormatDesc structure
 * \p desc and returns a handle to the new CUDA mipmapped array in \p *mipmappedArray.
 * \p numLevels specifies the number of mipmap levels to be allocated. This value is
 * clamped to the range [1, 1 + floor(log2(max(width, height, depth)))].
 *
 * The ::cudaChannelFormatDesc is defined as:
 * \code
    struct cudaChannelFormatDesc {
        int x, y, z, w;
        enum cudaChannelFormatKind f;
    };
    \endcode
 * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned,
 * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat.
 *
 * ::cudaMallocMipmappedArray() can allocate the following:
 *
 * - A 1D mipmapped array is allocated if the height and depth extents are both zero.
 * - A 2D mipmapped array is allocated if only the depth extent is zero.
 * - A 3D mipmapped array is allocated if all three extents are non-zero.
 * - A 1D layered CUDA mipmapped array is allocated if only the height extent is zero and
 * the cudaArrayLayered flag is set. Each layer is a 1D mipmapped array. The number of layers is 
 * determined by the depth extent.
 * - A 2D layered CUDA mipmapped array is allocated if all three extents are non-zero and 
 * the cudaArrayLayered flag is set. Each layer is a 2D mipmapped array. The number of layers is 
 * determined by the depth extent.
 * - A cubemap CUDA mipmapped array is allocated if all three extents are non-zero and the
 * cudaArrayCubemap flag is set. Width must be equal to height, and depth must be six.
 * The order of the six layers in memory is the same as that listed in ::cudaGraphicsCubeFace.
 * - A cubemap layered CUDA mipmapped array is allocated if all three extents are non-zero, and both,
 * cudaArrayCubemap and cudaArrayLayered flags are set. Width must be equal to height, and depth must be 
 * a multiple of six. A cubemap layered CUDA mipmapped array is a special type of 2D layered CUDA mipmapped
 * array that consists of a collection of cubemap mipmapped arrays. The first six layers represent the 
 * first cubemap mipmapped array, the next six layers form the second cubemap mipmapped array, and so on.
 *
 *
 * The \p flags parameter enables different options to be specified that affect
 * the allocation, as follows.
 * - ::cudaArrayDefault: This flag's value is defined to be 0 and provides default mipmapped array allocation
 * - ::cudaArrayLayered: Allocates a layered CUDA mipmapped array, with the depth extent indicating the number of layers
 * - ::cudaArrayCubemap: Allocates a cubemap CUDA mipmapped array. Width must be equal to height, and depth must be six.
 *   If the cudaArrayLayered flag is also set, depth must be a multiple of six.
 * - ::cudaArraySurfaceLoadStore: This flag indicates that individual mipmap levels of the CUDA mipmapped array 
 *   will be read from or written to using a surface reference.
 * - ::cudaArrayTextureGather: This flag indicates that texture gather operations will be performed on the CUDA 
 *   array. Texture gather can only be performed on 2D CUDA mipmapped arrays, and the gather operations are
 *   performed only on the most detailed mipmap level.
 * - ::cudaArraySparse: Allocates a CUDA mipmapped array without physical backing memory. The subregions within this sparse array
 *   can later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. This flag can only be used for creating 
 *   2D, 3D or 2D layered sparse CUDA mipmapped arrays. The physical backing memory must be allocated via ::cuMemCreate.
 * - ::cudaArrayDeferredMapping: Allocates a CUDA mipmapped array without physical backing memory. The entire array can
 *   later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. The physical backing memory must be allocated
 *   via ::cuMemCreate.
 *
 * The width, height and depth extents must meet certain size requirements as listed in the following table.
 * All values are specified in elements.
 *
 * \xmlonly
 * <table outputclass="xmlonly">
 * <tgroup cols="3" colsep="1" rowsep="1">
 * <colspec colname="c1" colwidth="1.0*"/>
 * <colspec colname="c2" colwidth="3.0*"/>
 * <colspec colname="c3" colwidth="3.0*"/>
 * <thead>
 * <row>
 * <entry>CUDA array type</entry>
 * <entry>Valid extents that must always be met {(width range in elements),
 * (height range), (depth range)}</entry>
 * <entry>Valid extents with cudaArraySurfaceLoadStore set {(width range in
 * elements), (height range), (depth range)}</entry>
 * </row>
 * </thead>
 * <tbody>
 * <row>
 * <entry>1D</entry>
 * <entry>{ (1,maxTexture1DMipmap), 0, 0 }</entry>
 * <entry>{ (1,maxSurface1D), 0, 0 }</entry>
 * </row>
 * <row>
 * <entry>2D</entry>
 * <entry>{ (1,maxTexture2DMipmap[0]), (1,maxTexture2DMipmap[1]), 0 }</entry>
 * <entry>{ (1,maxSurface2D[0]), (1,maxSurface2D[1]), 0 }</entry>
 * </row>
 * <row>
 * <entry>3D</entry>
 * <entry>{ (1,maxTexture3D[0]), (1,maxTexture3D[1]), (1,maxTexture3D[2]) }
 * OR { (1,maxTexture3DAlt[0]), (1,maxTexture3DAlt[1]),
 * (1,maxTexture3DAlt[2]) }</entry>
 * <entry>{ (1,maxSurface3D[0]), (1,maxSurface3D[1]), (1,maxSurface3D[2]) }</entry>
 * </row>
 * <row>
 * <entry>1D Layered</entry>
 * <entry>{ (1,maxTexture1DLayered[0]), 0, (1,maxTexture1DLayered[1]) }</entry>
 * <entry>{ (1,maxSurface1DLayered[0]), 0, (1,maxSurface1DLayered[1]) }</entry>
 * </row>
 * <row>
 * <entry>2D Layered</entry>
 * <entry>{ (1,maxTexture2DLayered[0]), (1,maxTexture2DLayered[1]),
 * (1,maxTexture2DLayered[2]) }</entry>
 * <entry>{ (1,maxSurface2DLayered[0]), (1,maxSurface2DLayered[1]),
 * (1,maxSurface2DLayered[2]) }</entry>
 * </row>
 * <row>
 * <entry>Cubemap</entry>
 * <entry>{ (1,maxTextureCubemap), (1,maxTextureCubemap), 6 }</entry>
 * <entry>{ (1,maxSurfaceCubemap), (1,maxSurfaceCubemap), 6 }</entry>
 * </row>
 * <row>
 * <entry>Cubemap Layered</entry>
 * <entry>{ (1,maxTextureCubemapLayered[0]), (1,maxTextureCubemapLayered[0]),
 * (1,maxTextureCubemapLayered[1]) }</entry>
 * <entry>{ (1,maxSurfaceCubemapLayered[0]), (1,maxSurfaceCubemapLayered[0]),
 * (1,maxSurfaceCubemapLayered[1]) }</entry>
 * </row>
 * </tbody>
 * </tgroup>
 * </table>
 * \endxmlonly
 *
 * \param mipmappedArray  - Pointer to allocated mipmapped array in device memory
 * \param desc            - Requested channel format
 * \param extent          - Requested allocation size (\p width field in elements)
 * \param numLevels       - Number of mipmap levels to allocate
 * \param flags           - Flags for extensions
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc3D, ::cudaMalloc, ::cudaMallocPitch, ::cudaFree,
 * ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::make_cudaExtent,
 * ::cuMipmappedArrayCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaMallocMipmappedArray(cudaMipmappedArray_t *mipmappedArray, const struct cudaChannelFormatDesc* desc, struct cudaExtent extent, unsigned int numLevels, unsigned int flags __dv(0));

/**
 * \brief Gets a mipmap level of a CUDA mipmapped array
 *
 * Returns in \p *levelArray a CUDA array that represents a single mipmap level
 * of the CUDA mipmapped array \p mipmappedArray.
 *
 * If \p level is greater than the maximum number of levels in this mipmapped array,
 * ::cudaErrorInvalidValue is returned.
 *
 * If \p mipmappedArray is NULL,
 * ::cudaErrorInvalidResourceHandle is returned.
 *
 * \param levelArray     - Returned mipmap level CUDA array
 * \param mipmappedArray - CUDA mipmapped array
 * \param level          - Mipmap level
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc3D, ::cudaMalloc, ::cudaMallocPitch, ::cudaFree,
 * ::cudaFreeArray,
 * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)",
 * ::cudaFreeHost, ::cudaHostAlloc,
 * ::make_cudaExtent,
 * ::cuMipmappedArrayGetLevel
 */
extern __host__ cudaError_t CUDARTAPI cudaGetMipmappedArrayLevel(cudaArray_t *levelArray, cudaMipmappedArray_const_t mipmappedArray, unsigned int level);

/**
 * \brief Copies data between 3D objects
 *
\code
struct cudaExtent {
  size_t width;
  size_t height;
  size_t depth;
};
struct cudaExtent make_cudaExtent(size_t w, size_t h, size_t d);

struct cudaPos {
  size_t x;
  size_t y;
  size_t z;
};
struct cudaPos make_cudaPos(size_t x, size_t y, size_t z);

struct cudaMemcpy3DParms {
  cudaArray_t           srcArray;
  struct cudaPos        srcPos;
  struct cudaPitchedPtr srcPtr;
  cudaArray_t           dstArray;
  struct cudaPos        dstPos;
  struct cudaPitchedPtr dstPtr;
  struct cudaExtent     extent;
  enum cudaMemcpyKind   kind;
};
\endcode
 *
 * ::cudaMemcpy3D() copies data betwen two 3D objects. The source and
 * destination objects may be in either host memory, device memory, or a CUDA
 * array. The source, destination, extent, and kind of copy performed is
 * specified by the ::cudaMemcpy3DParms struct which should be initialized to
 * zero before use:
\code
cudaMemcpy3DParms myParms = {0};
\endcode
 *
 * The struct passed to ::cudaMemcpy3D() must specify one of \p srcArray or
 * \p srcPtr and one of \p dstArray or \p dstPtr. Passing more than one
 * non-zero source or destination will cause ::cudaMemcpy3D() to return an
 * error.
 *
 * The \p srcPos and \p dstPos fields are optional offsets into the source and
 * destination objects and are defined in units of each object's elements. The
 * element for a host or device pointer is assumed to be <b>unsigned char</b>.
 *
 * The \p extent field defines the dimensions of the transferred area in
 * elements. If a CUDA array is participating in the copy, the extent is
 * defined in terms of that array's elements. If no CUDA array is
 * participating in the copy then the extents are defined in elements of
 * <b>unsigned char</b>.
 *
 * The \p kind field defines the direction of the copy. It must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * For ::cudaMemcpyHostToHost or ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost
 * passed as kind and cudaArray type passed as source or destination, if the kind
 * implies cudaArray type to be present on the host, ::cudaMemcpy3D() will
 * disregard that implication and silently correct the kind based on the fact that
 * cudaArray type can only be present on the device.
 *
 * If the source and destination are both arrays, ::cudaMemcpy3D() will return
 * an error if they do not have the same element size.
 *
 * The source and destination object may not overlap. If overlapping source
 * and destination objects are specified, undefined behavior will result.
 *
 * The source object must entirely contain the region defined by \p srcPos
 * and \p extent. The destination object must entirely contain the region
 * defined by \p dstPos and \p extent.
 *
 * ::cudaMemcpy3D() returns an error if the pitch of \p srcPtr or \p dstPtr
 * exceeds the maximum allowed. The pitch of a ::cudaPitchedPtr allocated
 * with ::cudaMalloc3D() will always be valid.
 *
 * \param p - 3D memory copy parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaMemset3D, ::cudaMemcpy3DAsync,
 * ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::make_cudaExtent, ::make_cudaPos,
 * ::cuMemcpy3D
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy3D(const struct cudaMemcpy3DParms *p);

/**
 * \brief Copies memory between devices
 *
 * Perform a 3D memory copy according to the parameters specified in
 * \p p.  See the definition of the ::cudaMemcpy3DPeerParms structure
 * for documentation of its parameters.
 *
 * Note that this function is synchronous with respect to the host only if
 * the source or destination of the transfer is host memory.  Note also 
 * that this copy is serialized with respect to all pending and future 
 * asynchronous work in to the current device, the copy's source device,
 * and the copy's destination device (use ::cudaMemcpy3DPeerAsync to avoid 
 * this synchronization).
 *
 * \param p - Parameters for the memory copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidPitchValue
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, ::cudaMemcpyPeerAsync,
 * ::cudaMemcpy3DPeerAsync,
 * ::cuMemcpy3DPeer
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeer(const struct cudaMemcpy3DPeerParms *p);

/**
 * \brief Copies data between 3D objects
 *
\code
struct cudaExtent {
  size_t width;
  size_t height;
  size_t depth;
};
struct cudaExtent make_cudaExtent(size_t w, size_t h, size_t d);

struct cudaPos {
  size_t x;
  size_t y;
  size_t z;
};
struct cudaPos make_cudaPos(size_t x, size_t y, size_t z);

struct cudaMemcpy3DParms {
  cudaArray_t           srcArray;
  struct cudaPos        srcPos;
  struct cudaPitchedPtr srcPtr;
  cudaArray_t           dstArray;
  struct cudaPos        dstPos;
  struct cudaPitchedPtr dstPtr;
  struct cudaExtent     extent;
  enum cudaMemcpyKind   kind;
};
\endcode
 *
 * ::cudaMemcpy3DAsync() copies data betwen two 3D objects. The source and
 * destination objects may be in either host memory, device memory, or a CUDA
 * array. The source, destination, extent, and kind of copy performed is
 * specified by the ::cudaMemcpy3DParms struct which should be initialized to
 * zero before use:
\code
cudaMemcpy3DParms myParms = {0};
\endcode
 *
 * The struct passed to ::cudaMemcpy3DAsync() must specify one of \p srcArray
 * or \p srcPtr and one of \p dstArray or \p dstPtr. Passing more than one
 * non-zero source or destination will cause ::cudaMemcpy3DAsync() to return an
 * error.
 *
 * The \p srcPos and \p dstPos fields are optional offsets into the source and
 * destination objects and are defined in units of each object's elements. The
 * element for a host or device pointer is assumed to be <b>unsigned char</b>.
 * For CUDA arrays, positions must be in the range [0, 2048) for any
 * dimension.
 *
 * The \p extent field defines the dimensions of the transferred area in
 * elements. If a CUDA array is participating in the copy, the extent is
 * defined in terms of that array's elements. If no CUDA array is
 * participating in the copy then the extents are defined in elements of
 * <b>unsigned char</b>.
 *
 * The \p kind field defines the direction of the copy. It must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * For ::cudaMemcpyHostToHost or ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost
 * passed as kind and cudaArray type passed as source or destination, if the kind
 * implies cudaArray type to be present on the host, ::cudaMemcpy3DAsync() will
 * disregard that implication and silently correct the kind based on the fact that
 * cudaArray type can only be present on the device.
 *
 * If the source and destination are both arrays, ::cudaMemcpy3DAsync() will
 * return an error if they do not have the same element size.
 *
 * The source and destination object may not overlap. If overlapping source
 * and destination objects are specified, undefined behavior will result.
 *
 * The source object must lie entirely within the region defined by \p srcPos
 * and \p extent. The destination object must lie entirely within the region
 * defined by \p dstPos and \p extent.
 *
 * ::cudaMemcpy3DAsync() returns an error if the pitch of \p srcPtr or
 * \p dstPtr exceeds the maximum allowed. The pitch of a
 * ::cudaPitchedPtr allocated with ::cudaMalloc3D() will always be valid.
 *
 * ::cudaMemcpy3DAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally
 * be associated to a stream by passing a non-zero \p stream argument. If
 * \p kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream
 * is non-zero, the copy may overlap with operations in other streams.
 *
 * The device version of this function only handles device to device copies and
 * cannot be given local or shared pointers.
 *
 * \param p      - 3D memory copy parameters
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaMemset3D, ::cudaMemcpy3D,
 * ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, :::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::make_cudaExtent, ::make_cudaPos,
 * ::cuMemcpy3DAsync
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy3DAsync(const struct cudaMemcpy3DParms *p, cudaStream_t stream __dv(0));

/**
 * \brief Copies memory between devices asynchronously.
 *
 * Perform a 3D memory copy according to the parameters specified in
 * \p p.  See the definition of the ::cudaMemcpy3DPeerParms structure
 * for documentation of its parameters.
 *
 * \param p      - Parameters for the memory copy
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidPitchValue
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, ::cudaMemcpyPeerAsync,
 * ::cudaMemcpy3DPeerAsync,
 * ::cuMemcpy3DPeerAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeerAsync(const struct cudaMemcpy3DPeerParms *p, cudaStream_t stream __dv(0));

/**
 * \brief Gets free and total device memory
 *
 * Returns in \p *total the total amount of memory available to the the current context.
 * Returns in \p *free the amount of memory on the device that is free according to the OS.
 * CUDA is not guaranteed to be able to allocate all of the memory that the OS reports as free.
 * In a multi-tenet situation, free estimate returned is prone to race condition where
 * a new allocation/free done by a different process or a different thread in the same
 * process between the time when free memory was estimated and reported, will result in
 * deviation in free value reported and actual free memory.
 *
 * The integrated GPU on Tegra shares memory with CPU and other component
 * of the SoC. The free and total values returned by the API excludes
 * the SWAP memory space maintained by the OS on some platforms.
 * The OS may move some of the memory pages into swap area as the GPU or
 * CPU allocate or access memory. See Tegra app note on how to calculate
 * total and free memory on Tegra.
 *
 * \param free  - Returned free memory in bytes
 * \param total - Returned total memory in bytes
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorLaunchFailure
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuMemGetInfo
 */
extern __host__ cudaError_t CUDARTAPI cudaMemGetInfo(size_t *free, size_t *total);

/**
 * \brief Gets info about the specified cudaArray
 * 
 * Returns in \p *desc, \p *extent and \p *flags respectively, the type, shape 
 * and flags of \p array.
 *
 * Any of \p *desc, \p *extent and \p *flags may be specified as NULL.
 *
 * \param desc   - Returned array type
 * \param extent - Returned array shape. 2D arrays will have depth of zero
 * \param flags  - Returned array flags
 * \param array  - The ::cudaArray to get info for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuArrayGetDescriptor,
 * ::cuArray3DGetDescriptor
 */
extern __host__ cudaError_t CUDARTAPI cudaArrayGetInfo(struct cudaChannelFormatDesc *desc, struct cudaExtent *extent, unsigned int *flags, cudaArray_t array);

/**
 * \brief Gets a CUDA array plane from a CUDA array
 *
 * Returns in \p pPlaneArray a CUDA array that represents a single format plane
 * of the CUDA array \p hArray.
 *
 * If \p planeIdx is greater than the maximum number of planes in this array or if the array does
 * not have a multi-planar format e.g: ::cudaChannelFormatKindNV12, then ::cudaErrorInvalidValue is returned.
 *
 * Note that if the \p hArray has format ::cudaChannelFormatKindNV12, then passing in 0 for \p planeIdx returns
 * a CUDA array of the same size as \p hArray but with one 8-bit channel and ::cudaChannelFormatKindUnsigned as its format kind.
 * If 1 is passed for \p planeIdx, then the returned CUDA array has half the height and width
 * of \p hArray with two 8-bit channels and ::cudaChannelFormatKindUnsigned as its format kind.
 *
 * \param pPlaneArray   - Returned CUDA array referenced by the \p planeIdx
 * \param hArray        - CUDA array
 * \param planeIdx      - Plane index
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 *
 * \sa
 * ::cuArrayGetPlane
 */
extern __host__ cudaError_t CUDARTAPI cudaArrayGetPlane(cudaArray_t *pPlaneArray, cudaArray_t hArray, unsigned int planeIdx);

/**
 * \brief Returns the memory requirements of a CUDA array
 *
 * Returns the memory requirements of a CUDA array in \p memoryRequirements
 * If the CUDA array is not allocated with flag ::cudaArrayDeferredMapping
 * ::cudaErrorInvalidValue will be returned.
 *
 * The returned value in ::cudaArrayMemoryRequirements::size
 * represents the total size of the CUDA array.
 * The returned value in ::cudaArrayMemoryRequirements::alignment
 * represents the alignment necessary for mapping the CUDA array.
 *
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 *
 * \param[out] memoryRequirements - Pointer to ::cudaArrayMemoryRequirements
 * \param[in] array - CUDA array to get the memory requirements of
 * \param[in] device - Device to get the memory requirements for
 * \sa ::cudaMipmappedArrayGetMemoryRequirements
 */
extern __host__ cudaError_t CUDARTAPI cudaArrayGetMemoryRequirements(struct cudaArrayMemoryRequirements  *memoryRequirements, cudaArray_t array, int device);

/**
 * \brief Returns the memory requirements of a CUDA mipmapped array
 *
 * Returns the memory requirements of a CUDA mipmapped array in \p memoryRequirements
 * If the CUDA mipmapped array is not allocated with flag ::cudaArrayDeferredMapping
 * ::cudaErrorInvalidValue will be returned.
 *
 * The returned value in ::cudaArrayMemoryRequirements::size
 * represents the total size of the CUDA mipmapped array.
 * The returned value in ::cudaArrayMemoryRequirements::alignment
 * represents the alignment necessary for mapping the CUDA mipmapped
 * array.
 *
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 *
 * \param[out] memoryRequirements - Pointer to ::cudaArrayMemoryRequirements
 * \param[in] mipmap - CUDA mipmapped array to get the memory requirements of
 * \param[in] device - Device to get the memory requirements for
 * \sa ::cudaArrayGetMemoryRequirements
 */
extern __host__ cudaError_t CUDARTAPI cudaMipmappedArrayGetMemoryRequirements(struct cudaArrayMemoryRequirements *memoryRequirements, cudaMipmappedArray_t mipmap, int device);

/**
 * \brief Returns the layout properties of a sparse CUDA array
 *
 * Returns the layout properties of a sparse CUDA array in \p sparseProperties.
 * If the CUDA array is not allocated with flag ::cudaArraySparse
 * ::cudaErrorInvalidValue will be returned.
 *
 * If the returned value in ::cudaArraySparseProperties::flags contains ::cudaArraySparsePropertiesSingleMipTail,
 * then ::cudaArraySparseProperties::miptailSize represents the total size of the array. Otherwise, it will be zero.
 * Also, the returned value in ::cudaArraySparseProperties::miptailFirstLevel is always zero.
 * Note that the \p array must have been allocated using ::cudaMallocArray or ::cudaMalloc3DArray. For CUDA arrays obtained
 * using ::cudaMipmappedArrayGetLevel, ::cudaErrorInvalidValue will be returned. Instead, ::cudaMipmappedArrayGetSparseProperties
 * must be used to obtain the sparse properties of the entire CUDA mipmapped array to which \p array belongs to.
 *
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 *
 * \param[out] sparseProperties - Pointer to return the ::cudaArraySparseProperties
 * \param[in] array             - The CUDA array to get the sparse properties of 
 *
 * \sa
 * ::cudaMipmappedArrayGetSparseProperties,
 * ::cuMemMapArrayAsync
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaArrayGetSparseProperties(struct cudaArraySparseProperties *sparseProperties, cudaArray_t array);
#endif

/**
 * \brief Returns the layout properties of a sparse CUDA mipmapped array
 *
 * Returns the sparse array layout properties in \p sparseProperties.
 * If the CUDA mipmapped array is not allocated with flag ::cudaArraySparse
 * ::cudaErrorInvalidValue will be returned.
 *
 * For non-layered CUDA mipmapped arrays, ::cudaArraySparseProperties::miptailSize returns the
 * size of the mip tail region. The mip tail region includes all mip levels whose width, height or depth
 * is less than that of the tile.
 * For layered CUDA mipmapped arrays, if ::cudaArraySparseProperties::flags contains ::cudaArraySparsePropertiesSingleMipTail,
 * then ::cudaArraySparseProperties::miptailSize specifies the size of the mip tail of all layers combined.
 * Otherwise, ::cudaArraySparseProperties::miptailSize specifies mip tail size per layer.
 * The returned value of ::cudaArraySparseProperties::miptailFirstLevel is valid only if ::cudaArraySparseProperties::miptailSize is non-zero.
 *
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 *
 * \param[out] sparseProperties - Pointer to return ::cudaArraySparseProperties
 * \param[in] mipmap            - The CUDA mipmapped array to get the sparse properties of
 *
 * \sa
 * ::cudaArrayGetSparseProperties,
 * ::cuMemMapArrayAsync
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaMipmappedArrayGetSparseProperties(struct cudaArraySparseProperties *sparseProperties, cudaMipmappedArray_t mipmap);
#endif

/**
 * \brief Copies data between host and device
 *
 * Copies \p count bytes from the memory area pointed to by \p src to the
 * memory area pointed to by \p dst, where \p kind specifies the direction
 * of the copy, and must be one of ::cudaMemcpyHostToHost,
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing. Calling
 * ::cudaMemcpy() with dst and src pointers that do not match the direction of
 * the copy results in an undefined behavior.
 *
 * \param dst   - Destination memory address
 * \param src   - Source memory address
 * \param count - Size in bytes to copy
 * \param kind  - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \note_sync
 * \note_memcpy
 *
 * \sa ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyDtoH,
 * ::cuMemcpyHtoD,
 * ::cuMemcpyDtoD,
 * ::cuMemcpy
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind);

/**
 * \brief Copies memory between two devices
 *
 * Copies memory from one device to memory on another device.  \p dst is the 
 * base device pointer of the destination memory and \p dstDevice is the 
 * destination device.  \p src is the base device pointer of the source memory 
 * and \p srcDevice is the source device.  \p count specifies the number of bytes 
 * to copy.
 *
 * Note that this function is asynchronous with respect to the host, but 
 * serialized with respect all pending and future asynchronous work in to the 
 * current device, \p srcDevice, and \p dstDevice (use ::cudaMemcpyPeerAsync 
 * to avoid this synchronization).
 *
 * \param dst       - Destination device pointer
 * \param dstDevice - Destination device
 * \param src       - Source device pointer
 * \param srcDevice - Source device
 * \param count     - Size of memory copy in bytes
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpyAsync, ::cudaMemcpyPeerAsync,
 * ::cudaMemcpy3DPeerAsync,
 * ::cuMemcpyPeer
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyPeer(void *dst, int dstDevice, const void *src, int srcDevice, size_t count);

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the memory
 * area pointed to by \p src to the memory area pointed to by \p dst, where
 * \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing. \p dpitch and
 * \p spitch are the widths in memory in bytes of the 2D arrays pointed to by
 * \p dst and \p src, including any padding added to the end of each row. The
 * memory areas may not overlap. \p width must not exceed either \p dpitch or
 * \p spitch. Calling ::cudaMemcpy2D() with \p dst and \p src pointers that do
 * not match the direction of the copy results in an undefined behavior.
 * ::cudaMemcpy2D() returns an error if \p dpitch or \p spitch exceeds
 * the maximum allowed.
 *
 * \param dst    - Destination memory address
 * \param dpitch - Pitch of destination memory
 * \param src    - Source memory address
 * \param spitch - Pitch of source memory
 * \param width  - Width of matrix transfer (columns in bytes)
 * \param height - Height of matrix transfer (rows)
 * \param kind   - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2D,
 * ::cuMemcpy2DUnaligned
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy2D(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind);

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the memory
 * area pointed to by \p src to the CUDA array \p dst starting at
 * \p hOffset rows and \p wOffset bytes from the upper left corner,
 * where \p kind specifies the direction of the copy, and must be one
 * of ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * \p spitch is the width in memory in bytes of the 2D array pointed to by
 * \p src, including any padding added to the end of each row. \p wOffset +
 * \p width must not exceed the width of the CUDA array \p dst. \p width must
 * not exceed \p spitch. ::cudaMemcpy2DToArray() returns an error if \p spitch
 * exceeds the maximum allowed.
 *
 * \param dst     - Destination memory address
 * \param wOffset - Destination starting X offset (columns in bytes)
 * \param hOffset - Destination starting Y offset (rows)
 * \param src     - Source memory address
 * \param spitch  - Pitch of source memory
 * \param width   - Width of matrix transfer (columns in bytes)
 * \param height  - Height of matrix transfer (rows)
 * \param kind    - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2D,
 * ::cuMemcpy2DUnaligned
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind);

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the CUDA
 * array \p src starting at \p hOffset rows and \p wOffset bytes from the
 * upper left corner to the memory area pointed to by \p dst, where
 * \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing. \p dpitch is the
 * width in memory in bytes of the 2D array pointed to by \p dst, including any
 * padding added to the end of each row. \p wOffset + \p width must not exceed
 * the width of the CUDA array \p src. \p width must not exceed \p dpitch.
 * ::cudaMemcpy2DFromArray() returns an error if \p dpitch exceeds the maximum
 * allowed.
 *
 * \param dst     - Destination memory address
 * \param dpitch  - Pitch of destination memory
 * \param src     - Source memory address
 * \param wOffset - Source starting X offset (columns in bytes)
 * \param hOffset - Source starting Y offset (rows)
 * \param width   - Width of matrix transfer (columns in bytes)
 * \param height  - Height of matrix transfer (rows)
 * \param kind    - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2D,
 * ::cuMemcpy2DUnaligned
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArray(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind);

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the CUDA
 * array \p src starting at \p hOffsetSrc rows and \p wOffsetSrc bytes from the
 * upper left corner to the CUDA array \p dst starting at \p hOffsetDst rows
 * and \p wOffsetDst bytes from the upper left corner, where \p kind
 * specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * \p wOffsetDst + \p width must not exceed the width of the CUDA array \p dst.
 * \p wOffsetSrc + \p width must not exceed the width of the CUDA array \p src.
 *
 * \param dst        - Destination memory address
 * \param wOffsetDst - Destination starting X offset (columns in bytes)
 * \param hOffsetDst - Destination starting Y offset (rows)
 * \param src        - Source memory address
 * \param wOffsetSrc - Source starting X offset (columns in bytes)
 * \param hOffsetSrc - Source starting Y offset (rows)
 * \param width      - Width of matrix transfer (columns in bytes)
 * \param height     - Height of matrix transfer (rows)
 * \param kind       - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2D,
 * ::cuMemcpy2DUnaligned
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t width, size_t height, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice));

/**
 * \brief Copies data to the given symbol on the device
 *
 * Copies \p count bytes from the memory area pointed to by \p src
 * to the memory area pointed to by \p offset bytes from the start of symbol
 * \p symbol. The memory areas may not overlap. \p symbol is a variable that
 * resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of
 * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault
 * is only allowed on systems that support unified virtual addressing.
 *
 * \param symbol - Device symbol address
 * \param src    - Source memory address
 * \param count  - Size in bytes to copy
 * \param offset - Offset from start of symbol in bytes
 * \param kind   - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorInvalidMemcpyDirection,
 * ::cudaErrorNoKernelImageForDevice
 * \notefnerr
 * \note_sync
 * \note_string_api_deprecation
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray,  ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy,
 * ::cuMemcpyHtoD,
 * ::cuMemcpyDtoD
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbol(const void *symbol, const void *src, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice));


/**
 * \brief Copies data from the given symbol on the device
 *
 * Copies \p count bytes from the memory area pointed to by \p offset bytes
 * from the start of symbol \p symbol to the memory area pointed to by \p dst.
 * The memory areas may not overlap. \p symbol is a variable that
 * resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of
 * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault
 * is only allowed on systems that support unified virtual addressing.
 *
 * \param dst    - Destination memory address
 * \param symbol - Device symbol address
 * \param count  - Size in bytes to copy
 * \param offset - Offset from start of symbol in bytes
 * \param kind   - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorInvalidMemcpyDirection,
 * ::cudaErrorNoKernelImageForDevice
 * \notefnerr
 * \note_sync
 * \note_string_api_deprecation
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy,
 * ::cuMemcpyDtoH,
 * ::cuMemcpyDtoD
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbol(void *dst, const void *symbol, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost));


/**
 * \brief Copies data between host and device
 *
 * Copies \p count bytes from the memory area pointed to by \p src to the
 * memory area pointed to by \p dst, where \p kind specifies the
 * direction of the copy, and must be one of ::cudaMemcpyHostToHost,
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * 
 * The memory areas may not overlap. Calling ::cudaMemcpyAsync() with \p dst and
 * \p src pointers that do not match the direction of the copy results in an
 * undefined behavior.
 *
 * ::cudaMemcpyAsync() is asynchronous with respect to the host, so the call
 * may return before the copy is complete. The copy can optionally be
 * associated to a stream by passing a non-zero \p stream argument. If \p kind
 * is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and the \p stream is
 * non-zero, the copy may overlap with operations in other streams.
 *
 * The device version of this function only handles device to device copies and
 * cannot be given local or shared pointers.
 *
 * \param dst    - Destination memory address
 * \param src    - Source memory address
 * \param count  - Size in bytes to copy
 * \param kind   - Type of transfer
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyAsync,
 * ::cuMemcpyDtoHAsync,
 * ::cuMemcpyHtoDAsync,
 * ::cuMemcpyDtoDAsync
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpyAsync(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/**
 * \brief Copies memory between two devices asynchronously.
 *
 * Copies memory from one device to memory on another device.  \p dst is the 
 * base device pointer of the destination memory and \p dstDevice is the 
 * destination device.  \p src is the base device pointer of the source memory 
 * and \p srcDevice is the source device.  \p count specifies the number of bytes 
 * to copy.
 *
 * Note that this function is asynchronous with respect to the host and all work
 * on other devices.
 *
 * \param dst       - Destination device pointer
 * \param dstDevice - Destination device
 * \param src       - Source device pointer
 * \param srcDevice - Source device
 * \param count     - Size of memory copy in bytes
 * \param stream    - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync,
 * ::cudaMemcpy3DPeerAsync,
 * ::cuMemcpyPeerAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyPeerAsync(void *dst, int dstDevice, const void *src, int srcDevice, size_t count, cudaStream_t stream __dv(0));

/**
 * \brief Performs a batch of memory copies asynchronously.
 *
 * Performs a batch of memory copies. The batch as a whole executes in stream order but copies within a
 * batch are not guaranteed to execute in any specific order. This API only supports pointer-to-pointer copies.
 * For copies involving CUDA arrays, please see ::cudaMemcpy3DBatchAsync.
 *
 * Performs memory copies from source buffers specified in \p srcs to destination buffers specified in \p dsts.
 * The size of each copy is specified in \p sizes. All three arrays must be of the same length as specified
 * by \p count. Since there are no ordering guarantees for copies within a batch, specifying any dependent copies
 * within a batch will result in undefined behavior.
 *
 * Every copy in the batch has to be associated with a set of attributes specified in the \p attrs array.
 * Each entry in this array can apply to more than one copy. This can be done by specifying in the \p attrsIdxs array,
 * the index of the first copy that the corresponding entry in the \p attrs array applies to. Both \p attrs and
 * \p attrsIdxs must be of the same length as specified by \p numAttrs. For example, if a batch has 10 copies listed
 * in dst/src/sizes, the first 6 of which have one set of attributes and the remaining 4 another, then \p numAttrs
 * will be 2, \p attrsIdxs will be {0, 6} and \p attrs will contains the two sets of attributes. Note that the first entry
 * in \p attrsIdxs must always be 0. Also, each entry must be greater than the previous entry and the last entry should be
 * less than \p count. Furthermore, \p numAttrs must be lesser than or equal to \p count.
 *
 * The ::cudaMemcpyAttributes::srcAccessOrder indicates the source access ordering to be observed for copies associated
 * with the attribute. If the source access order is set to ::cudaMemcpySrcAccessOrderStream, then the source will
 * be accessed in stream order. If the source access order is set to ::cudaMemcpySrcAccessOrderDuringApiCall then
 * it indicates that access to the source pointer can be out of stream order and all accesses must be complete before the
 * API call returns. This flag is suited for ephemeral sources (ex., stack variables) when it's known that no prior
 * operations in the stream can be accessing the memory and also that the lifetime of the memory is limited to the scope
 * that the source variable was declared in. Specifying this flag allows the driver to optimize the copy and removes the
 * need for the user to synchronize the stream after the API call. If the source access order is set to
 * ::cudaMemcpySrcAccessOrderAny then it indicates that access to the source pointer can be out of stream order and the
 * accesses can happen even after the API call returns. This flag is suited for host pointers allocated
 * outside CUDA (ex., via malloc) when it's known that no prior operations in the stream can be accessing the memory.
 * Specifying this flag allows the driver to optimize the copy on certain platforms. Each memcpy operation in the batch
 * must have a valid ::cudaMemcpyAttributes corresponding to it including the appropriate srcAccessOrder setting,
 * otherwise the API will return ::cudaErrorInvalidValue.
 *
 * The ::cudaMemcpyAttributes::srcLocHint and ::cudaMemcpyAttributes::dstLocHint allows applications to specify hint locations
 * for operands of a copy when the operand doesn't have a fixed location. That is, these hints are
 * only applicable for managed memory pointers on devices where ::cudaDevAttrConcurrentManagedAccess is true or
 * system-allocated pageable memory on devices where ::cudaDevAttrPageableMemoryAccess is true.
 * For other cases, these hints are ignored.
 *
 * The ::cudaMemcpyAttributes::flags field can be used to specify certain flags for copies. Setting the
 * ::cudaMemcpyFlagPreferOverlapWithCompute flag indicates that the associated copies should preferably overlap with
 * any compute work. Note that this flag is a hint and can be ignored depending on the platform and other parameters of the copy.
 *
 *
 * \param dsts          - Array of destination pointers.
 * \param srcs          - Array of memcpy source pointers.
 * \param sizes         - Array of sizes for memcpy operations.
 * \param count         - Size of \p dsts, \p srcs and \p sizes arrays
 * \param attrs         - Array of memcpy attributes. 
 * \param attrsIdxs     - Array of indices to specify which copies each entry in the \p attrs array applies to.
 *                        The attributes specified in attrs[k] will be applied to copies starting from attrsIdxs[k]
 *                        through attrsIdxs[k+1] - 1. Also attrs[numAttrs-1] will apply to copies starting from
 *                        attrsIdxs[numAttrs-1] through count - 1.
 * \param numAttrs      - Size of \p attrs and \p attrsIdxs arrays.
 * \param hStream       - The stream to enqueue the operations in. Must not be legacy NULL stream.
 *
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_async
 * \note_memcpy
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyBatchAsync(void *const *dsts, const void *const *srcs, const size_t *sizes, size_t count, struct cudaMemcpyAttributes *attrs, size_t *attrsIdxs, size_t numAttrs, cudaStream_t stream);

/**
 * \brief Performs a batch of 3D memory copies asynchronously.
 *
 * Performs a batch of memory copies. The batch as a whole executes in stream order but copies within a
 * batch are not guaranteed to execute in any specific order. Note that this means specifying any dependent
 * copies within a batch will result in undefined behavior.
 *
 * Performs memory copies as specified in the \p opList array. The length of this array is specified in \p numOps.
 * Each entry in this array describes a copy operation. This includes among other things, the source and destination
 * operands for the copy as specified in ::cudaMemcpy3DBatchOp::src and ::cudaMemcpy3DBatchOp::dst respectively.
 * The source and destination operands of a copy can either be a pointer or a CUDA array. The width, height and depth
 * of a copy is specified in ::cudaMemcpy3DBatchOp::extent. The width, height and depth of a copy are specified in
 * elements and must not be zero. For pointer-to-pointer copies, the element size is considered to be 1. For pointer
 * to CUDA array or vice versa copies, the element size is determined by the CUDA array. For CUDA array to CUDA array copies,
 * the element size of the two CUDA arrays must match.
 *
 * For a given operand, if ::cudaMemcpy3DOperand::type is specified as ::cudaMemcpyOperandTypePointer, then
 * ::cudaMemcpy3DOperand::op::ptr will be used. The ::cudaMemcpy3DOperand::op::ptr::ptr field must contain the pointer where
 * the copy should begin. The ::cudaMemcpy3DOperand::op::ptr::rowLength field specifies the length of each row in elements and
 * must either be zero or be greater than or equal to the width of the copy specified in ::cudaMemcpy3DBatchOp::extent::width.
 * The ::cudaMemcpy3DOperand::op::ptr::layerHeight field specifies the height of each layer and must either be
 * zero or be greater than or equal to the height of the copy specified in ::cudaMemcpy3DBatchOp::extent::height.
 * When either of these values is zero, that aspect of the operand is considered to be tightly packed according to the copy extent.
 * For managed memory pointers on devices where ::cudaDevAttrConcurrentManagedAccess is true or system-allocated pageable memory
 * on devices where ::cudaDevAttrPageableMemoryAccess is true, the ::cudaMemcpy3DOperand::op::ptr::locHint field can be used to hint
 * the location of the operand.
 *
 * If an operand's type is specified as ::cudaMemcpyOperandTypeArray, then ::cudaMemcpy3DOperand::op::array will be used.
 * The ::cudaMemcpy3DOperand::op::array::array field specifies the CUDA array and ::cudaMemcpy3DOperand::op::array::offset specifies
 * the 3D offset into that array where the copy begins.
 *
 * The ::cudaMemcpyAttributes::srcAccessOrder indicates the source access ordering to be observed for copies associated
 * with the attribute. If the source access order is set to ::cudaMemcpySrcAccessOrderStream, then the source will
 * be accessed in stream order. If the source access order is set to ::cudaMemcpySrcAccessOrderDuringApiCall then
 * it indicates that access to the source pointer can be out of stream order and all accesses must be complete before the
 * API call returns. This flag is suited for ephemeral sources (ex., stack variables) when it's known that no prior
 * operations in the stream can be accessing the memory and also that the lifetime of the memory is limited to the scope
 * that the source variable was declared in. Specifying this flag allows the driver to optimize the copy and removes the
 * need for the user to synchronize the stream after the API call. If the source access order is set to
 * ::cudaMemcpySrcAccessOrderAny then it indicates that access to the source pointer can be out of stream order and the
 * accesses can happen even after the API call returns. This flag is suited for host pointers allocated
 * outside CUDA (ex., via malloc) when it's known that no prior operations in the stream can be accessing the memory.
 * Specifying this flag allows the driver to optimize the copy on certain platforms. Each memcopy operation in \p opList
 * must have a valid srcAccessOrder setting, otherwise this API will return ::cudaErrorInvalidValue.
 *
 * The ::cudaMemcpyAttributes::flags field can be used to specify certain flags for copies. Setting the
 * ::cudaMemcpyFlagPreferOverlapWithCompute flag indicates that the associated copies should preferably overlap with
 * any compute work. Note that this flag is a hint and can be ignored depending on the platform and other parameters of the copy.
 *
 *
 * \param numOps     - Total number of memcpy operations. 
 * \param opList     - Array of size \p numOps containing the actual memcpy operations. 
 * \param flags      - Flags for future use, must be zero now.
 * \param hStream    - The stream to enqueue the operations in. Must not be default NULL stream.
 *
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_async
 * \note_memcpy
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DBatchAsync(size_t numOps, struct cudaMemcpy3DBatchOp *opList, unsigned long long flags, cudaStream_t stream);

/**
 * Performs asynchronous memory copy operation with the specified attributes.
 *
 * Performs asynchronous memory copy operation where \p dst and \p src are
 * the destination and source pointers respectively. \p size specifies
 * the number of bytes to copy. \p attr specifies the attributes for the copy and
 * \p hStream specifies the stream to enqueue the operation in.
 * 
 * For more information regarding the attributes, please refer to ::cudaMemcpyAttributes and it's usage desciption in::cudaMemcpyBatchAsync
 *
 * \param dst - Destination device pointer
 * \param src - Source device pointer
 * \param size - Number of bytes to copy
 * \param attr - Attributes for the copy
 * \param hStream - Stream to enqueue the operation in
 * 
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_async
 * \note_memcpy
 *
 * \sa ::cudaMemcpyBatchAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyWithAttributesAsync(void *dst, const void *src, size_t size, struct cudaMemcpyAttributes *attr, cudaStream_t stream);

/**
 * Performs 3D asynchronous memory copy with the specified attributes.
 *
 * Performs the copy operation specified in \p op.
 * \p flags specifies the flags for the copy and \p hStream specifies the stream to enqueue the operation in.
 *
 * For more information regarding the operation, please refer to ::cudaMemcpy3DBatchOp and it's usage desciption in::cudaMemcpy3DBatchAsync
 *
 * \param op - Operation to perform
 * \param flags - Flags for the copy, must be zero now.
 * \param hStream - Stream to enqueue the operation in
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_async
 * \note_memcpy
 *
 * \sa ::cudaMemcpy3DBatchAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DWithAttributesAsync(struct cudaMemcpy3DBatchOp *op, unsigned long long flags, cudaStream_t stream);

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the memory
 * area pointed to by \p src to the memory area pointed to by \p dst, where
 * \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * \p dpitch and \p spitch are the widths in memory in bytes of the 2D arrays
 * pointed to by \p dst and \p src, including any padding added to the end of
 * each row. The memory areas may not overlap. \p width must not exceed either
 * \p dpitch or \p spitch.
 *
 * Calling ::cudaMemcpy2DAsync() with \p dst and \p src pointers that do not
 * match the direction of the copy results in an undefined behavior.
 * ::cudaMemcpy2DAsync() returns an error if \p dpitch or \p spitch is greater
 * than the maximum allowed.
 *
 * ::cudaMemcpy2DAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally
 * be associated to a stream by passing a non-zero \p stream argument. If
 * \p kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and
 * \p stream is non-zero, the copy may overlap with operations in other
 * streams.
 *
 * The device version of this function only handles device to device copies and
 * cannot be given local or shared pointers.
 *
 * \param dst    - Destination memory address
 * \param dpitch - Pitch of destination memory
 * \param src    - Source memory address
 * \param spitch - Pitch of source memory
 * \param width  - Width of matrix transfer (columns in bytes)
 * \param height - Height of matrix transfer (rows)
 * \param kind   - Type of transfer
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2DAsync
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy2DAsync(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the memory
 * area pointed to by \p src to the CUDA array \p dst starting at \p hOffset
 * rows and \p wOffset bytes from the upper left corner, where \p kind specifies
 * the direction of the copy, and must be one of ::cudaMemcpyHostToHost,
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * \p spitch is the width in memory in bytes of the 2D array pointed to by
 * \p src, including any padding added to the end of each row. \p wOffset +
 * \p width must not exceed the width of the CUDA array \p dst. \p width must
 * not exceed \p spitch. ::cudaMemcpy2DToArrayAsync() returns an error if
 * \p spitch exceeds the maximum allowed.
 *
 * ::cudaMemcpy2DToArrayAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally
 * be associated to a stream by passing a non-zero \p stream argument. If
 * \p kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and
 * \p stream is non-zero, the copy may overlap with operations in other
 * streams.
 *
 * \param dst     - Destination memory address
 * \param wOffset - Destination starting X offset (columns in bytes)
 * \param hOffset - Destination starting Y offset (rows)
 * \param src     - Source memory address
 * \param spitch  - Pitch of source memory
 * \param width   - Width of matrix transfer (columns in bytes)
 * \param height  - Height of matrix transfer (rows)
 * \param kind    - Type of transfer
 * \param stream  - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 *
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2DAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/**
 * \brief Copies data between host and device
 *
 * Copies a matrix (\p height rows of \p width bytes each) from the CUDA
 * array \p src starting at \p hOffset rows and \p wOffset bytes from the
 * upper left corner to the memory area pointed to by \p dst,
 * where \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 * \p dpitch is the width in memory in bytes of the 2D
 * array pointed to by \p dst, including any padding added to the end of each
 * row. \p wOffset + \p width must not exceed the width of the CUDA array
 * \p src. \p width must not exceed \p dpitch. ::cudaMemcpy2DFromArrayAsync()
 * returns an error if \p dpitch exceeds the maximum allowed.
 *
 * ::cudaMemcpy2DFromArrayAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally be
 * associated to a stream by passing a non-zero \p stream argument. If \p kind
 * is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream is
 * non-zero, the copy may overlap with operations in other streams.
 *
 * \param dst     - Destination memory address
 * \param dpitch  - Pitch of destination memory
 * \param src     - Source memory address
 * \param wOffset - Source starting X offset (columns in bytes)
 * \param hOffset - Source starting Y offset (rows)
 * \param width   - Width of matrix transfer (columns in bytes)
 * \param height  - Height of matrix transfer (rows)
 * \param kind    - Type of transfer
 * \param stream  - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidPitchValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 * \note_memcpy
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 *
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpy2DAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/**
 * \brief Copies data to the given symbol on the device
 *
 * Copies \p count bytes from the memory area pointed to by \p src
 * to the memory area pointed to by \p offset bytes from the start of symbol
 * \p symbol. The memory areas may not overlap. \p symbol is a variable that
 * resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer
 * is inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * ::cudaMemcpyToSymbolAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally
 * be associated to a stream by passing a non-zero \p stream argument. If
 * \p kind is ::cudaMemcpyHostToDevice and \p stream is non-zero, the copy
 * may overlap with operations in other streams.
 *
 * \param symbol - Device symbol address
 * \param src    - Source memory address
 * \param count  - Size in bytes to copy
 * \param offset - Offset from start of symbol in bytes
 * \param kind   - Type of transfer
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorInvalidMemcpyDirection,
 * ::cudaErrorNoKernelImageForDevice
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_string_api_deprecation
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyAsync,
 * ::cuMemcpyHtoDAsync,
 * ::cuMemcpyDtoDAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbolAsync(const void *symbol, const void *src, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/**
 * \brief Copies data from the given symbol on the device
 *
 * Copies \p count bytes from the memory area pointed to by \p offset bytes
 * from the start of symbol \p symbol to the memory area pointed to by \p dst.
 * The memory areas may not overlap. \p symbol is a variable that resides in
 * global or constant memory space. \p kind can be either
 * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer
 * is inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * ::cudaMemcpyFromSymbolAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally be
 * associated to a stream by passing a non-zero \p stream argument. If \p kind
 * is ::cudaMemcpyDeviceToHost and \p stream is non-zero, the copy may overlap
 * with operations in other streams.
 *
 * \param dst    - Destination memory address
 * \param symbol - Device symbol address
 * \param count  - Size in bytes to copy
 * \param offset - Offset from start of symbol in bytes
 * \param kind   - Type of transfer
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorInvalidMemcpyDirection,
 * ::cudaErrorNoKernelImageForDevice
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_string_api_deprecation
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync,
 * ::cuMemcpyAsync,
 * ::cuMemcpyDtoHAsync,
 * ::cuMemcpyDtoDAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbolAsync(void *dst, const void *symbol, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));


/**
 * \brief Initializes or sets device memory to a value
 *
 * Fills the first \p count bytes of the memory area pointed to by \p devPtr
 * with the constant byte value \p value.
 *
 * Note that this function is asynchronous with respect to the host unless
 * \p devPtr refers to pinned host memory.
 *
 * \param devPtr - Pointer to device memory
 * \param value  - Value to set for each byte of specified memory
 * \param count  - Size in bytes to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_memset
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuMemsetD8,
 * ::cuMemsetD16,
 * ::cuMemsetD32
 */
extern __host__ cudaError_t CUDARTAPI cudaMemset(void *devPtr, int value, size_t count);

/**
 * \brief Initializes or sets device memory to a value
 *
 * Sets to the specified value \p value a matrix (\p height rows of \p width
 * bytes each) pointed to by \p dstPtr. \p pitch is the width in bytes of the
 * 2D array pointed to by \p dstPtr, including any padding added to the end
 * of each row. This function performs fastest when the pitch is one that has
 * been passed back by ::cudaMallocPitch().
 *
 * Note that this function is asynchronous with respect to the host unless
 * \p devPtr refers to pinned host memory.
 *
 * \param devPtr - Pointer to 2D device memory
 * \param pitch  - Pitch in bytes of 2D device memory(Unused if \p height is 1)
 * \param value  - Value to set for each byte of specified memory
 * \param width  - Width of matrix set (columns in bytes)
 * \param height - Height of matrix set (rows)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_memset
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemset, ::cudaMemset3D, ::cudaMemsetAsync,
 * ::cudaMemset2DAsync, ::cudaMemset3DAsync,
 * ::cuMemsetD2D8,
 * ::cuMemsetD2D16,
 * ::cuMemsetD2D32
 */
extern __host__ cudaError_t CUDARTAPI cudaMemset2D(void *devPtr, size_t pitch, int value, size_t width, size_t height);

/**
 * \brief Initializes or sets device memory to a value
 *
 * Initializes each element of a 3D array to the specified value \p value.
 * The object to initialize is defined by \p pitchedDevPtr. The \p pitch field
 * of \p pitchedDevPtr is the width in memory in bytes of the 3D array pointed
 * to by \p pitchedDevPtr, including any padding added to the end of each row.
 * The \p xsize field specifies the logical width of each row in bytes, while
 * the \p ysize field specifies the height of each 2D slice in rows.
 * The \p pitch field of \p pitchedDevPtr is ignored when \p height and \p depth 
 * are both equal to 1. 
 *
 * The extents of the initialized region are specified as a \p width in bytes,
 * a \p height in rows, and a \p depth in slices.
 *
 * Extents with \p width greater than or equal to the \p xsize of
 * \p pitchedDevPtr may perform significantly faster than extents narrower
 * than the \p xsize. Secondarily, extents with \p height equal to the
 * \p ysize of \p pitchedDevPtr will perform faster than when the \p height is
 * shorter than the \p ysize.
 *
 * This function performs fastest when the \p pitchedDevPtr has been allocated
 * by ::cudaMalloc3D().
 *
 * Note that this function is asynchronous with respect to the host unless
 * \p pitchedDevPtr refers to pinned host memory.
 *
 * \param pitchedDevPtr - Pointer to pitched device memory
 * \param value         - Value to set for each byte of specified memory
 * \param extent        - Size parameters for where to set device memory (\p width field in bytes)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_memset
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemset, ::cudaMemset2D,
 * ::cudaMemsetAsync, ::cudaMemset2DAsync, ::cudaMemset3DAsync,
 * ::cudaMalloc3D, ::make_cudaPitchedPtr,
 * ::make_cudaExtent
 */
extern __host__ cudaError_t CUDARTAPI cudaMemset3D(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent);

/**
 * \brief Initializes or sets device memory to a value
 *
 * Fills the first \p count bytes of the memory area pointed to by \p devPtr
 * with the constant byte value \p value.
 *
 * ::cudaMemsetAsync() is asynchronous with respect to the host, so
 * the call may return before the memset is complete. The operation can optionally
 * be associated to a stream by passing a non-zero \p stream argument.
 * If \p stream is non-zero, the operation may overlap with operations in other streams.
 *
 * The device version of this function only handles device to device copies and
 * cannot be given local or shared pointers.
 *
 * \param devPtr - Pointer to device memory
 * \param value  - Value to set for each byte of specified memory
 * \param count  - Size in bytes to set
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_memset
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemset, ::cudaMemset2D, ::cudaMemset3D,
 * ::cudaMemset2DAsync, ::cudaMemset3DAsync,
 * ::cuMemsetD8Async,
 * ::cuMemsetD16Async,
 * ::cuMemsetD32Async
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemsetAsync(void *devPtr, int value, size_t count, cudaStream_t stream __dv(0));

/**
 * \brief Initializes or sets device memory to a value
 *
 * Sets to the specified value \p value a matrix (\p height rows of \p width
 * bytes each) pointed to by \p dstPtr. \p pitch is the width in bytes of the
 * 2D array pointed to by \p dstPtr, including any padding added to the end
 * of each row. This function performs fastest when the pitch is one that has
 * been passed back by ::cudaMallocPitch().
 *
 * ::cudaMemset2DAsync() is asynchronous with respect to the host, so
 * the call may return before the memset is complete. The operation can optionally
 * be associated to a stream by passing a non-zero \p stream argument.
 * If \p stream is non-zero, the operation may overlap with operations in other streams.
 *
 * The device version of this function only handles device to device copies and
 * cannot be given local or shared pointers.
 *
 * \param devPtr - Pointer to 2D device memory
 * \param pitch  - Pitch in bytes of 2D device memory(Unused if \p height is 1)
 * \param value  - Value to set for each byte of specified memory
 * \param width  - Width of matrix set (columns in bytes)
 * \param height - Height of matrix set (rows)
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_memset
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemset, ::cudaMemset2D, ::cudaMemset3D,
 * ::cudaMemsetAsync, ::cudaMemset3DAsync,
 * ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16Async,
 * ::cuMemsetD2D32Async
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset2DAsync(void *devPtr, size_t pitch, int value, size_t width, size_t height, cudaStream_t stream __dv(0));

/**
 * \brief Initializes or sets device memory to a value
 *
 * Initializes each element of a 3D array to the specified value \p value.
 * The object to initialize is defined by \p pitchedDevPtr. The \p pitch field
 * of \p pitchedDevPtr is the width in memory in bytes of the 3D array pointed
 * to by \p pitchedDevPtr, including any padding added to the end of each row.
 * The \p xsize field specifies the logical width of each row in bytes, while
 * the \p ysize field specifies the height of each 2D slice in rows.
 * The \p pitch field of \p pitchedDevPtr is ignored when \p height and \p depth 
 * are both equal to 1. 
 *
 * The extents of the initialized region are specified as a \p width in bytes,
 * a \p height in rows, and a \p depth in slices.
 *
 * Extents with \p width greater than or equal to the \p xsize of
 * \p pitchedDevPtr may perform significantly faster than extents narrower
 * than the \p xsize. Secondarily, extents with \p height equal to the
 * \p ysize of \p pitchedDevPtr will perform faster than when the \p height is
 * shorter than the \p ysize.
 *
 * This function performs fastest when the \p pitchedDevPtr has been allocated
 * by ::cudaMalloc3D().
 *
 * ::cudaMemset3DAsync() is asynchronous with respect to the host, so
 * the call may return before the memset is complete. The operation can optionally
 * be associated to a stream by passing a non-zero \p stream argument.
 * If \p stream is non-zero, the operation may overlap with operations in other streams.
 *
 * The device version of this function only handles device to device copies and
 * cannot be given local or shared pointers.
 *
 * \param pitchedDevPtr - Pointer to pitched device memory
 * \param value         - Value to set for each byte of specified memory
 * \param extent        - Size parameters for where to set device memory (\p width field in bytes)
 * \param stream - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_memset
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemset, ::cudaMemset2D, ::cudaMemset3D,
 * ::cudaMemsetAsync, ::cudaMemset2DAsync,
 * ::cudaMalloc3D, ::make_cudaPitchedPtr,
 * ::make_cudaExtent
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset3DAsync(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent, cudaStream_t stream __dv(0));

/**
 * \brief Finds the address associated with a CUDA symbol
 *
 * Returns in \p *devPtr the address of symbol \p symbol on the device.
 * \p symbol is a variable that resides in global or constant memory space.
 * If \p symbol cannot be found, or if \p symbol is not declared in the
 * global or constant memory space, \p *devPtr is unchanged and the error
 * ::cudaErrorInvalidSymbol is returned.
 *
 * \param devPtr - Return device pointer associated with symbol
 * \param symbol - Device symbol address
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorNoKernelImageForDevice
 * \notefnerr
 * \note_string_api_deprecation
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * \ref ::cudaGetSymbolAddress(void**, const T&) "cudaGetSymbolAddress (C++ API)",
 * \ref ::cudaGetSymbolSize(size_t*, const void*) "cudaGetSymbolSize (C API)",
 * ::cuModuleGetGlobal
 */
extern __host__ cudaError_t CUDARTAPI cudaGetSymbolAddress(void **devPtr, const void *symbol);

/**
 * \brief Finds the size of the object associated with a CUDA symbol
 *
 * Returns in \p *size the size of symbol \p symbol. \p symbol is a variable that
 * resides in global or constant memory space. If \p symbol cannot be found, or
 * if \p symbol is not declared in global or constant memory space, \p *size is
 * unchanged and the error ::cudaErrorInvalidSymbol is returned.
 *
 * \param size   - Size of object associated with symbol
 * \param symbol - Device symbol address
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidSymbol,
 * ::cudaErrorNoKernelImageForDevice
 * \notefnerr
 * \note_string_api_deprecation
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * \ref ::cudaGetSymbolAddress(void**, const void*) "cudaGetSymbolAddress (C API)",
 * \ref ::cudaGetSymbolSize(size_t*, const T&) "cudaGetSymbolSize (C++ API)",
 * ::cuModuleGetGlobal
 */
extern __host__ cudaError_t CUDARTAPI cudaGetSymbolSize(size_t *size, const void *symbol);


/**
 * \brief Prefetches memory to the specified destination location
 *
 * Prefetches memory to the specified destination location.  \p devPtr is the
 * base device pointer of the memory to be prefetched and \p location specifies the
 * destination location. \p count specifies the number of bytes to copy. \p stream
 * is the stream in which the operation is enqueued. The memory range must refer
 * to managed memory allocated via ::cudaMallocManaged or declared via __managed__ variables, 
 * or it may also refer to memory allocated from a managed memory pool,
 * or it may also refer to system-allocated memory on systems with non-zero
 * cudaDevAttrPageableMemoryAccess.
 * 
 * Specifying ::cudaMemLocationTypeDevice for ::cudaMemLocation::type will prefetch memory to GPU
 * specified by device ordinal ::cudaMemLocation::id which must have non-zero value for the device attribute
 * ::concurrentManagedAccess. Additionally, \p stream must be associated with a device
 * that has a non-zero value for the device attribute ::concurrentManagedAccess.
 * Specifying ::cudaMemLocationTypeHost as ::cudaMemLocation::type will prefetch data to host memory.
 * Applications can request prefetching memory to a specific host NUMA node by specifying
 * ::cudaMemLocationTypeHostNuma for ::cudaMemLocation::type and a valid host NUMA node id in ::cudaMemLocation::id
 * Users can also request prefetching memory to the host NUMA node closest to the current thread's CPU by specifying
 * ::cudaMemLocationTypeHostNumaCurrent for ::cudaMemLocation::type. Note when ::cudaMemLocation::type is etiher
 * ::cudaMemLocationTypeHost OR ::cudaMemLocationTypeHostNumaCurrent, ::cudaMemLocation::id will be ignored.
 *
 * The start address and end address of the memory range will be rounded down and rounded up
 * respectively to be aligned to CPU page size before the prefetch operation is enqueued
 * in the stream.
 *
 * If no physical memory has been allocated for this region, then this memory region
 * will be populated and mapped on the destination device. If there's insufficient
 * memory to prefetch the desired region, the Unified Memory driver may evict pages from other
 * ::cudaMallocManaged allocations to host memory in order to make room. Device memory
 * allocated using ::cudaMalloc or ::cudaMallocArray will not be evicted.
 *
 * By default, any mappings to the previous location of the migrated pages are removed and
 * mappings for the new location are only setup on the destination location. The exact behavior however
 * also depends on the settings applied to this memory range via ::cuMemAdvise as described
 * below:
 *
 * If ::cudaMemAdviseSetReadMostly was set on any subset of this memory range,
 * then that subset will create a read-only copy of the pages on destination location.
 * If however the destination location is a host NUMA node, then any pages of that subset
 * that are already in another host NUMA node will be transferred to the destination.
 *
 * If ::cudaMemAdviseSetPreferredLocation was called on any subset of this memory
 * range, then the pages will be migrated to \p location even if \p location is not the
 * preferred location of any pages in the memory range.
 *
 * If ::cudaMemAdviseSetAccessedBy was called on any subset of this memory range,
 * then mappings to those pages from all the appropriate processors are updated to
 * refer to the new location if establishing such a mapping is possible. Otherwise,
 * those mappings are cleared.
 *
 * Note that this API is not required for functionality and only serves to improve performance
 * by allowing the application to migrate data to a suitable location before it is accessed.
 * Memory accesses to this range are always coherent and are allowed even when the data is
 * actively being migrated.
 *
 * Note that this function is asynchronous with respect to the host and all work
 * on other devices.
 *
 * \param devPtr    - Pointer to be prefetched
 * \param count     - Size in bytes
 * \param location  - location to prefetch to
 * \param flags     - flags for future use, must be zero now. 
 * \param stream    - Stream to enqueue prefetch operation
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync,
 * ::cudaMemcpy3DPeerAsync, ::cudaMemAdvise, ::cuMemPrefetchAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchAsync(const void *devPtr, size_t count, struct cudaMemLocation location, unsigned int flags, cudaStream_t stream __dv(0));

/**
 * \brief Performs a batch of memory prefetches asynchronously
 *
 * Performs a batch of memory prefetches. The batch as a whole executes in stream order
 * but operations within a batch are not guaranteed to execute in any specific order.
 * All devices in the system must have a non-zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess otherwise the API will return an error.
 * 
 * The semantics of the individual prefetch operations are as described in ::cudaMemPrefetchAsync.
 * 
 * Performs memory prefetch on address ranges specified in \p dptrs and \p sizes.
 * Both arrays must be of the same length as specified by \p count. Each memory range specified
 * must refer to managed memory allocated via ::cudaMallocManaged or declared via
 * __managed__ variables or it may also refer to system-allocated memory when all devices
 * have a non-zero value for ::cudaDevAttrPageableMemoryAccess. The prefetch location for
 * every operation in the batch is specified in the \p prefetchLocs array. Each entry in
 * this array can apply to more than one operation. This can be done by specifying in the
 * \p prefetchLocIdxs array, the index of the first prefetch operation that the corresponding entry
 * in the \p prefetchLocs array applies to. Both \p prefetchLocs and \p prefetchLocIdxs must be of
 * the same length as specified by \p numPrefetchLocs. For example, if a batch has 10 prefetches listed
 * in dptrs/sizes, the first 4 of which are to be prefetched to one location and the remaining 6 are to be prefetched
 * to another, then \p numPrefetchLocs will be 2, \p prefetchLocIdxs will be {0, 4} and \p prefetchLocs
 * will contain the two locations. Note the first entry in \p prefetchLocIdxs must always be 0.
 * Also, each entry must be greater than the previous entry and the last entry should be less than \p count.
 * Furthermore, \p numPrefetchLocs must be lesser than or equal to \p count.
 *
 * \param dptrs           - Array of pointers to be prefetched
 * \param sizes           - Array of sizes for memory prefetch operations.
 * \param count           - Size of \p dptrs and \p sizes arrays.
 * \param prefetchLocs    - Array of locations to prefetch to.
 * \param prefetchLocIdxs - Array of indices to specify which operands each entry in the \p prefetchLocs array applies to.
 *                          The locations specified in prefetchLocs[k] will be applied to copies starting from  prefetchLocIdxs[k]
 *                          through  prefetchLocIdxs[k+1] - 1. Also prefetchLocs[numPrefetchLocs - 1] will apply to prefetches starting from
 *                          prefetchLocIdxs[numPrefetchLocs - 1] through count - 1.
 * \param numPrefetchLocs - Size of \p prefetchLocs and \p prefetchLocIdxs arrays.
 * \param flags           - Flags reserved for future use. Must be zero.
 * \param hStream         - The stream to enqueue the operations in. Must not be legacy NULL stream.
 *
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchBatchAsync(void **dptrs, size_t *sizes, size_t count,
                                                              struct cudaMemLocation *prefetchLocs, size_t *prefetchLocIdxs, size_t numPrefetchLocs,
                                                              unsigned long long flags, cudaStream_t stream);

/**
 * \brief Performs a batch of memory discards asynchronously
 *
 * Performs a batch of memory discards. The batch as a whole executes in stream order
 * but operations within a batch are not guaranteed to execute in any specific order.
 * All devices in the system must have a non-zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess otherwise the API will return an error.
 * 
 * Discarding a memory range informs the driver that the contents of that range are no longer useful.
 * Discarding memory ranges allows the driver to optimize certain data migrations and can also help
 * reduce memory pressure. This operation can be undone on any part of the range by either writing to it
 * or prefetching it via ::cudaMemPrefetchAsync or ::cudaMemPrefetchBatchAsync. Reading from a discarded range,
 * without a subsequent write or prefetch to that part of the range, will return an indeterminate value.
 * Note that any reads, writes or prefetches to any part of the memory range that occur simultaneously with
 * the discard operation result in undefined behavior.
 *
 * Performs memory discard on address ranges specified in \p dptrs and \p sizes.
 * Both arrays must be of the same length as specified by \p count. Each memory range
 * specified must refer to managed memory allocated via ::cudaMallocManaged or declared
 * via __managed__ variables or it may also refer to system-allocated memory when all devices
 * have a non-zero value for ::cudaDevAttrPageableMemoryAccess.
 *
 * \param dptrs   - Array of pointers to be discarded
 * \param sizes   - Array of sizes for memory discard operations.
 * \param count   - Size of \p dptrs and \p sizes arrays.
 * \param flags   - Flags reserved for future use. Must be zero.
 * \param hStream - The stream to enqueue the operations in. Must not be legacy NULL stream.
 *
 */
extern __host__ cudaError_t CUDARTAPI cudaMemDiscardBatchAsync(void **dptrs, size_t *sizes, size_t count, unsigned long long flags, cudaStream_t stream);

/**
 * \brief Performs a batch of memory discards and prefetches asynchronously
 *
 * Performs a batch of memory discards followed by prefetches. The batch as a whole executes
 * in stream order but operations within a batch are not guaranteed to execute in any specific order.
 * All devices in the system must have a non-zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess otherwise the API will return an error.
 * 
 * Calling ::cudaMemDiscardAndPrefetchBatchAsync is semantically equivalent to calling
 * ::cudaMemDiscardBatchAsync followed by ::cudaMemPrefetchBatchAsync, but is more optimal.
 * For more details on what discarding and prefetching imply, please refer to ::cudaMemDiscardBatchAsync
 * and ::cudaMemPrefetchBatchAsync respectively. Note that any reads, writes or prefetches to any part
 * of the memory range that occur simultaneously with this combined discard+prefetch operation
 * result in undefined behavior.
 *
 * Performs memory discard and prefetch on address ranges specified in \p dptrs and \p sizes.
 * Both arrays must be of the same length as specified by \p count. Each memory range specified
 * must refer to managed memory allocated via ::cudaMallocManaged or declared via
 * __managed__ variables or it may also refer to system-allocated memory when all devices
 * have a non-zero value for ::cudaDevAttrPageableMemoryAccess. Every operation in the batch
 * has to be associated with a valid location to prefetch the address range to and specified in
 * the \p prefetchLocs array. Each entry in this array can apply to more than one operation.
 * This can be done by specifying in the \p prefetchLocIdxs array, the index of the first
 * operation that the corresponding entry in the \p prefetchLocs array applies to.
 * Both \p prefetchLocs and \p prefetchLocIdxs must be of the same length as specified by
 * \p numPrefetchLocs. For example, if a batch has 10 operations listed in dptrs/sizes,
 * the first 6 of which are to be prefetched to one location and the remaining 4 are to be
 * prefetched to another, then \p numPrefetchLocs will be 2, \p prefetchLocIdxs will be {0, 6}
 * and \p prefetchLocs will contain the two set of locations. Note the first entry in
 * \p prefetchLocIdxs must always be 0. Also, each entry must be greater than the previous
 * entry and the last entry should be less than \p count. Furthermore, \p numPrefetchLocs
 * must be lesser than or equal to \p count.
 *
 * \param dptrs           - Array of pointers to be discarded
 * \param sizes           - Array of sizes for memory discard operations.
 * \param count           - Size of \p dptrs and \p sizes arrays.
 * \param prefetchLocs    - Array of locations to prefetch to.
 * \param prefetchLocIdxs - Array of indices to specify which operands each entry in the \p prefetchLocs array applies to.
 *                          The locations specified in prefetchLocs[k] will be applied to operations starting from  prefetchLocIdxs[k]
 *                          through prefetchLocIdxs[k+1] - 1. Also prefetchLocs[numPrefetchLocs - 1] will apply to copies starting from
 *                          prefetchLocIdxs[numPrefetchLocs - 1] through count - 1.
 * \param numPrefetchLocs - Size of \p prefetchLocs and \p prefetchLocIdxs arrays.
 * \param flags           - Flags reserved for future use. Must be zero.
 * \param hStream         - The stream to enqueue the operations in. Must not be legacy NULL stream.
 *
 */
extern __host__ cudaError_t CUDARTAPI cudaMemDiscardAndPrefetchBatchAsync(void **dptrs, size_t *sizes, size_t count,
                                                              struct cudaMemLocation *prefetchLocs, size_t *prefetchLocIdxs, size_t numPrefetchLocs,
                                                              unsigned long long flags, cudaStream_t stream);


/**
 * \brief Advise about the usage of a given memory range
 *
 * Advise the Unified Memory subsystem about the usage pattern for the memory range
 * starting at \p devPtr with a size of \p count bytes. The start address and end address of the memory
 * range will be rounded down and rounded up respectively to be aligned to CPU page size before the
 * advice is applied. The memory range must refer to managed memory allocated via ::cudaMallocManaged
 * or declared via __managed__ variables. The memory range could also refer to system-allocated pageable
 * memory provided it represents a valid, host-accessible region of memory and all additional constraints
 * imposed by \p advice as outlined below are also satisfied. Specifying an invalid system-allocated pageable
 * memory range results in an error being returned.
 *
 * The \p advice parameter can take the following values:
 * - ::cudaMemAdviseSetReadMostly: This implies that the data is mostly going to be read
 * from and only occasionally written to. Any read accesses from any processor to this region will create a
 * read-only copy of at least the accessed pages in that processor's memory. Additionally, if ::cudaMemPrefetchAsync
 * or ::cudaMemPrefetchAsync is called on this region, it will create a read-only copy of the data on the destination processor.
 * If the target location for ::cudaMemPrefetchAsync is a host NUMA node and a read-only copy already exists on
 * another host NUMA node, that copy will be migrated to the targeted host NUMA node.
 * If any processor writes to this region, all copies of the corresponding page will be invalidated
 * except for the one where the write occurred. If the writing processor is the CPU and the preferred location of
 * the page is a host NUMA node, then the page will also be migrated to that host NUMA node. The \p location argument is ignored for this advice.
 * Note that for a page to be read-duplicated, the accessing processor must either be the CPU or a GPU
 * that has a non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess.
 * Also, if a context is created on a device that does not have the device attribute
 * ::cudaDevAttrConcurrentManagedAccess set, then read-duplication will not occur until
 * all such contexts are destroyed.
 * If the memory region refers to valid system-allocated pageable memory, then the accessing device must
 * have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess for a read-only
 * copy to be created on that device. Note however that if the accessing device also has a non-zero value for the
 * device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, then setting this advice
 * will not create a read-only copy when that device accesses this memory region.
 *
 * - ::cudaMemAdviceUnsetReadMostly:  Undoes the effect of ::cudaMemAdviseSetReadMostly and also prevents the
 * Unified Memory driver from attempting heuristic read-duplication on the memory range. Any read-duplicated
 * copies of the data will be collapsed into a single copy. The location for the collapsed
 * copy will be the preferred location if the page has a preferred location and one of the read-duplicated
 * copies was resident at that location. Otherwise, the location chosen is arbitrary.
 * Note: The \p location argument is ignored for this advice.
 *
 * - ::cudaMemAdviseSetPreferredLocation: This advice sets the preferred location for the
 * data to be the memory belonging to \p location. When ::cudaMemLocation::type is ::cudaMemLocationTypeHost,
 * ::cudaMemLocation::id is ignored and the preferred location is set to be host memory. To set the preferred location
 * to a specific host NUMA node, applications must set ::cudaMemLocation::type to ::cudaMemLocationTypeHostNuma and
 * ::cudaMemLocation::id must specify the NUMA ID of the host NUMA node. If ::cudaMemLocation::type is set to ::cudaMemLocationTypeHostNumaCurrent,
 * ::cudaMemLocation::id will be ignored and the host NUMA node closest to the calling thread's CPU will be used as the preferred location.
 * If ::cudaMemLocation::type is a ::cudaMemLocationTypeDevice, then ::cudaMemLocation::id must be a valid device ordinal
 * and the device must have a non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess.
 * Setting the preferred location does not cause data to migrate to that location immediately. Instead, it guides the migration policy
 * when a fault occurs on that memory region. If the data is already in its preferred location and the
 * faulting processor can establish a mapping without requiring the data to be migrated, then
 * data migration will be avoided. On the other hand, if the data is not in its preferred location
 * or if a direct mapping cannot be established, then it will be migrated to the processor accessing
 * it. It is important to note that setting the preferred location does not prevent data prefetching
 * done using ::cudaMemPrefetchAsync.
 * Having a preferred location can override the page thrash detection and resolution logic in the Unified
 * Memory driver. Normally, if a page is detected to be constantly thrashing between for example host and device
 * memory, the page may eventually be pinned to host memory by the Unified Memory driver. But
 * if the preferred location is set as device memory, then the page will continue to thrash indefinitely.
 * If ::cudaMemAdviseSetReadMostly is also set on this memory region or any subset of it, then the
 * policies associated with that advice will override the policies of this advice, unless read accesses from
 * \p location will not result in a read-only copy being created on that procesor as outlined in description for
 * the advice ::cudaMemAdviseSetReadMostly.
 * If the memory region refers to valid system-allocated pageable memory, and ::cudaMemLocation::type is ::cudaMemLocationTypeDevice
 * then ::cudaMemLocation::id must be a valid device that has a non-zero alue for the device attribute ::cudaDevAttrPageableMemoryAccess.
 *
 * - ::cudaMemAdviseUnsetPreferredLocation: Undoes the effect of ::cudaMemAdviseSetPreferredLocation
 * and changes the preferred location to none. The \p location argument is ignored for this advice.
 *
 * - ::cudaMemAdviseSetAccessedBy: This advice implies that the data will be accessed by processor \p location.
 * The ::cudaMemLocation::type must be either ::cudaMemLocationTypeDevice with ::cudaMemLocation::id representing a valid device
 * ordinal or ::cudaMemLocationTypeHost and ::cudaMemLocation::id will be ignored. All other location types are invalid.
 * If ::cudaMemLocation::id is a GPU, then the device attribute ::cudaDevAttrConcurrentManagedAccess must be non-zero.
 * This advice does not cause data migration and has no impact on the location of the data per se. Instead,
 * it causes the data to always be mapped in the specified processor's page tables, as long as the
 * location of the data permits a mapping to be established. If the data gets migrated for any reason,
 * the mappings are updated accordingly.
 * This advice is recommended in scenarios where data locality is not important, but avoiding faults is.
 * Consider for example a system containing multiple GPUs with peer-to-peer access enabled, where the
 * data located on one GPU is occasionally accessed by peer GPUs. In such scenarios, migrating data
 * over to the other GPUs is not as important because the accesses are infrequent and the overhead of
 * migration may be too high. But preventing faults can still help improve performance, and so having
 * a mapping set up in advance is useful. Note that on CPU access of this data, the data may be migrated
 * to host memory because the CPU typically cannot access device memory directly. Any GPU that had the
 * ::cudaMemAdviseSetAccessedBy flag set for this data will now have its mapping updated to point to the
 * page in host memory.
 * If ::cudaMemAdviseSetReadMostly is also set on this memory region or any subset of it, then the
 * policies associated with that advice will override the policies of this advice. Additionally, if the
 * preferred location of this memory region or any subset of it is also \p location, then the policies
 * associated with ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION will override the policies of this advice.
 * If the memory region refers to valid system-allocated pageable memory, and ::cudaMemLocation::type is ::cudaMemLocationTypeDevice
 * then device in ::cudaMemLocation::id must have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess.
 * Additionally, if ::cudaMemLocation::id has a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables,
 * then this call has no effect.
 *
 * - ::CU_MEM_ADVISE_UNSET_ACCESSED_BY: Undoes the effect of ::cudaMemAdviseSetAccessedBy. Any mappings to
 * the data from \p location may be removed at any time causing accesses to result in non-fatal page faults.
 * If the memory region refers to valid system-allocated pageable memory, and ::cudaMemLocation::type is ::cudaMemLocationTypeDevice
 * then device in ::cudaMemLocation::id must have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess.
 * Additionally, if ::cudaMemLocation::id has a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables,
 * then this call has no effect.
 *
 * \param devPtr   - Pointer to memory to set the advice for
 * \param count    - Size in bytes of the memory range
 * \param advice   - Advice to be applied for the specified memory range
 * \param location - location to apply the advice for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync,
 * ::cudaMemcpy3DPeerAsync, ::cudaMemPrefetchAsync,
 * ::cuMemAdvise
 */
extern __host__ cudaError_t CUDARTAPI cudaMemAdvise(const void *devPtr, size_t count, enum cudaMemoryAdvise advice, struct cudaMemLocation location);

/**
* \brief Query an attribute of a given memory range
*
* Query an attribute about the memory range starting at \p devPtr with a size of \p count bytes. The
* memory range must refer to managed memory allocated via ::cudaMallocManaged or declared via
* __managed__ variables.
*
* The \p attribute parameter can take the following values:
* - ::cudaMemRangeAttributeReadMostly: If this attribute is specified, \p data will be interpreted
* as a 32-bit integer, and \p dataSize must be 4. The result returned will be 1 if all pages in the given
* memory range have read-duplication enabled, or 0 otherwise.
* - ::cudaMemRangeAttributePreferredLocation: If this attribute is specified, \p data will be
* interpreted as a 32-bit integer, and \p dataSize must be 4. The result returned will be a GPU device
* id if all pages in the memory range have that GPU as their preferred location, or it will be cudaCpuDeviceId
* if all pages in the memory range have the CPU as their preferred location, or it will be cudaInvalidDeviceId
* if either all the pages don't have the same preferred location or some of the pages don't have a
* preferred location at all. Note that the actual location of the pages in the memory range at the time of
* the query may be different from the preferred location.
* - ::cudaMemRangeAttributeAccessedBy: If this attribute is specified, \p data will be interpreted
* as an array of 32-bit integers, and \p dataSize must be a non-zero multiple of 4. The result returned
* will be a list of device ids that had ::cudaMemAdviceSetAccessedBy set for that entire memory range.
* If any device does not have that advice set for the entire memory range, that device will not be included.
* If \p data is larger than the number of devices that have that advice set for that memory range,
* cudaInvalidDeviceId will be returned in all the extra space provided. For ex., if \p dataSize is 12
* (i.e. \p data has 3 elements) and only device 0 has the advice set, then the result returned will be
* { 0, cudaInvalidDeviceId, cudaInvalidDeviceId }. If \p data is smaller than the number of devices that have
* that advice set, then only as many devices will be returned as can fit in the array. There is no
* guarantee on which specific devices will be returned, however.
* - ::cudaMemRangeAttributeLastPrefetchLocation: If this attribute is specified, \p data will be
* interpreted as a 32-bit integer, and \p dataSize must be 4. The result returned will be the last location
* to which all pages in the memory range were prefetched explicitly via ::cudaMemPrefetchAsync. This will either be
* a GPU id or cudaCpuDeviceId depending on whether the last location for prefetch was a GPU or the CPU
* respectively. If any page in the memory range was never explicitly prefetched or if all pages were not
* prefetched to the same location, cudaInvalidDeviceId will be returned. Note that this simply returns the
* last location that the applicaton requested to prefetch the memory range to. It gives no indication as to
* whether the prefetch operation to that location has completed or even begun.
* - ::cudaMemRangeAttributePreferredLocationType: If this attribute is specified, \p data will be
* interpreted as a ::cudaMemLocationType, and \p dataSize must be sizeof(cudaMemLocationType). The ::cudaMemLocationType returned will be
* ::cudaMemLocationTypeDevice if all pages in the memory range have the same GPU as their preferred location, or ::cudaMemLocationType
* will be ::cudaMemLocationTypeHost if all pages in the memory range have the CPU as their preferred location, or or it will be ::cudaMemLocationTypeHostNuma
* if all the pages in the memory range have the same host NUMA node ID as their preferred location or it will be ::cudaMemLocationTypeInvalid
* if either all the pages don't have the same preferred location or some of the pages don't have a preferred location at all.
* Note that the actual location type of the pages in the memory range at the time of the query may be different from the preferred location type.
*  - ::cudaMemRangeAttributePreferredLocationId: If this attribute is specified, \p data will be
* interpreted as a 32-bit integer, and \p dataSize must be 4. If the ::cudaMemRangeAttributePreferredLocationType query for the same address range
* returns ::cudaMemLocationTypeDevice, it will be a valid device ordinal or if it returns ::cudaMemLocationTypeHostNuma, it will be a valid host NUMA node ID
* or if it returns any other location type, the id should be ignored.
* - ::cudaMemRangeAttributeLastPrefetchLocationType: If this attribute is specified, \p data will be
* interpreted as a ::cudaMemLocationType, and \p dataSize must be sizeof(cudaMemLocationType). The result returned will be the last location type
* to which all pages in the memory range were prefetched explicitly via ::cuMemPrefetchAsync. The ::cudaMemLocationType returned
* will be ::cudaMemLocationTypeDevice if the last prefetch location was the GPU or ::cudaMemLocationTypeHost if it was the CPU or ::cudaMemLocationTypeHostNuma if
* the last prefetch location was a specific host NUMA node. If any page in the memory range was never explicitly prefetched or if all pages were not
* prefetched to the same location, ::CUmemLocationType will be ::cudaMemLocationTypeInvalid.
* Note that this simply returns the last location type that the application requested to prefetch the memory range to. It gives no indication as to
* whether the prefetch operation to that location has completed or even begun.
*  - ::cudaMemRangeAttributeLastPrefetchLocationId: If this attribute is specified, \p data will be
* interpreted as a 32-bit integer, and \p dataSize must be 4. If the ::cudaMemRangeAttributeLastPrefetchLocationType query for the same address range
* returns ::cudaMemLocationTypeDevice, it will be a valid device ordinal or if it returns ::cudaMemLocationTypeHostNuma, it will be a valid host NUMA node ID
* or if it returns any other location type, the id should be ignored.
*
* \param data      - A pointers to a memory location where the result
*                    of each attribute query will be written to.
* \param dataSize  - Array containing the size of data
* \param attribute - The attribute to query
* \param devPtr    - Start of the range to query
* \param count     - Size of the range to query
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemRangeGetAttributes, ::cudaMemPrefetchAsync,
 * ::cudaMemAdvise,
 * ::cuMemRangeGetAttribute
 */
extern __host__ cudaError_t CUDARTAPI cudaMemRangeGetAttribute(void *data, size_t dataSize, enum cudaMemRangeAttribute attribute, const void *devPtr, size_t count);

/**
 * \brief Query attributes of a given memory range.
 *
 * Query attributes of the memory range starting at \p devPtr with a size of \p count bytes. The
 * memory range must refer to managed memory allocated via ::cudaMallocManaged or declared via
 * __managed__ variables. The \p attributes array will be interpreted to have \p numAttributes
 * entries. The \p dataSizes array will also be interpreted to have \p numAttributes entries.
 * The results of the query will be stored in \p data.
 *
 * The list of supported attributes are given below. Please refer to ::cudaMemRangeGetAttribute for
 * attribute descriptions and restrictions.
 *
 * - ::cudaMemRangeAttributeReadMostly
 * - ::cudaMemRangeAttributePreferredLocation
 * - ::cudaMemRangeAttributeAccessedBy
 * - ::cudaMemRangeAttributeLastPrefetchLocation
 * - :: cudaMemRangeAttributePreferredLocationType
 * - :: cudaMemRangeAttributePreferredLocationId
 * - :: cudaMemRangeAttributeLastPrefetchLocationType
 * - :: cudaMemRangeAttributeLastPrefetchLocationId
 *
 * \param data          - A two-dimensional array containing pointers to memory
 *                        locations where the result of each attribute query will be written to.
 * \param dataSizes     - Array containing the sizes of each result
 * \param attributes    - An array of attributes to query
 *                        (numAttributes and the number of attributes in this array should match)
 * \param numAttributes - Number of attributes to query
 * \param devPtr        - Start of the range to query
 * \param count         - Size of the range to query
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemRangeGetAttribute, ::cudaMemAdvise,
 * ::cudaMemPrefetchAsync,
 * ::cuMemRangeGetAttributes
 */
extern __host__ cudaError_t CUDARTAPI cudaMemRangeGetAttributes(void **data, size_t *dataSizes, enum cudaMemRangeAttribute *attributes, size_t numAttributes, const void *devPtr, size_t count);

/** @} */ /* END CUDART_MEMORY */

/**
 * \defgroup CUDART_MEMORY_DEPRECATED Memory Management [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated memory management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes deprecated memory management functions of the CUDA runtime
 * application programming interface.
 *
 * Some functions have overloaded C++ API template versions documented separately in the
 * \ref CUDART_HIGHLEVEL "C++ API Routines" module.
 *
 * @{
 */

/**
 * \brief Copies data between host and device
 *
 * \deprecated
 *
 * Copies \p count bytes from the memory area pointed to by \p src to the
 * CUDA array \p dst starting at \p hOffset rows and \p wOffset bytes from
 * the upper left corner, where \p kind specifies the direction
 * of the copy, and must be one of ::cudaMemcpyHostToHost,
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * \param dst     - Destination memory address
 * \param wOffset - Destination starting X offset (columns in bytes)
 * \param hOffset - Destination starting Y offset (rows)
 * \param src     - Source memory address
 * \param count   - Size in bytes to copy
 * \param kind    - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyHtoA,
 * ::cuMemcpyDtoA
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind);

/**
 * \brief Copies data between host and device
 *
 * \deprecated
 *
 * Copies \p count bytes from the CUDA array \p src starting at \p hOffset rows
 * and \p wOffset bytes from the upper left corner to the memory area pointed to
 * by \p dst, where \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * \param dst     - Destination memory address
 * \param src     - Source memory address
 * \param wOffset - Source starting X offset (columns in bytes)
 * \param hOffset - Source starting Y offset (rows)
 * \param count   - Size in bytes to copy
 * \param kind    - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_sync
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray,
 * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyAtoH,
 * ::cuMemcpyAtoD
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyFromArray(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind);

/**
 * \brief Copies data between host and device
 *
 * \deprecated
 *
 * Copies \p count bytes from the CUDA array \p src starting at \p hOffsetSrc
 * rows and \p wOffsetSrc bytes from the upper left corner to the CUDA array
 * \p dst starting at \p hOffsetDst rows and \p wOffsetDst bytes from the upper
 * left corner, where \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * \param dst        - Destination memory address
 * \param wOffsetDst - Destination starting X offset (columns in bytes)
 * \param hOffsetDst - Destination starting Y offset (rows)
 * \param src        - Source memory address
 * \param wOffsetSrc - Source starting X offset (columns in bytes)
 * \param hOffsetSrc - Source starting Y offset (rows)
 * \param count      - Size in bytes to copy
 * \param kind       - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray,
 * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyAtoA
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t count, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice));

/**
 * \brief Copies data between host and device
 *
 * \deprecated
 *
 * Copies \p count bytes from the memory area pointed to by \p src to the
 * CUDA array \p dst starting at \p hOffset rows and \p wOffset bytes from
 * the upper left corner, where \p kind specifies the
 * direction of the copy, and must be one of ::cudaMemcpyHostToHost,
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * ::cudaMemcpyToArrayAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally
 * be associated to a stream by passing a non-zero \p stream argument. If \p
 * kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream
 * is non-zero, the copy may overlap with operations in other streams.
 *
 * \param dst     - Destination memory address
 * \param wOffset - Destination starting X offset (columns in bytes)
 * \param hOffset - Destination starting Y offset (rows)
 * \param src     - Source memory address
 * \param count   - Size in bytes to copy
 * \param kind    - Type of transfer
 * \param stream  - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray,
 * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyHtoAAsync,
 * ::cuMemcpy2DAsync
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/**
 * \brief Copies data between host and device
 *
 * \deprecated
 *
 * Copies \p count bytes from the CUDA array \p src starting at \p hOffset rows
 * and \p wOffset bytes from the upper left corner to the memory area pointed to
 * by \p dst, where \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * ::cudaMemcpyFromArrayAsync() is asynchronous with respect to the host, so
 * the call may return before the copy is complete. The copy can optionally
 * be associated to a stream by passing a non-zero \p stream argument. If \p
 * kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream
 * is non-zero, the copy may overlap with operations in other streams.
 *
 * \param dst     - Destination memory address
 * \param src     - Source memory address
 * \param wOffset - Source starting X offset (columns in bytes)
 * \param hOffset - Source starting Y offset (rows)
 * \param count   - Size in bytes to copy
 * \param kind    - Type of transfer
 * \param stream  - Stream identifier
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidMemcpyDirection
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray,
 * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray,
 * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync,
 * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync,
 * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync,
 * ::cuMemcpyAtoHAsync,
 * ::cuMemcpy2DAsync
 */
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyFromArrayAsync(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));

/** @} */ /* END CUDART_MEMORY_DEPRECATED */

/**
 * \defgroup CUDART_MEMORY_POOLS Stream Ordered Memory Allocator 
 *
 * ___MANBRIEF___ Functions for performing allocation and free operations in stream order.
 *                Functions for controlling the behavior of the underlying allocator.
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 * 
 *
 * @{
 *
 * \section CUDART_MEMORY_POOLS_overview overview
 *
 * The asynchronous allocator allows the user to allocate and free in stream order.
 * All asynchronous accesses of the allocation must happen between
 * the stream executions of the allocation and the free. If the memory is accessed
 * outside of the promised stream order, a use before allocation / use after free error
 * will cause undefined behavior.
 *
 * The allocator is free to reallocate the memory as long as it can guarantee
 * that compliant memory accesses will not overlap temporally.
 * The allocator may refer to internal stream ordering as well as inter-stream dependencies
 * (such as CUDA events and null stream dependencies) when establishing the temporal guarantee.
 * The allocator may also insert inter-stream dependencies to establish the temporal guarantee.
 *
 * \section CUDART_MEMORY_POOLS_support Supported Platforms
 *
 * Whether or not a device supports the integrated stream ordered memory allocator
 * may be queried by calling ::cudaDeviceGetAttribute() with the device attribute
 * ::cudaDevAttrMemoryPoolsSupported.
 */

/**
 * \brief Allocates memory with stream ordered semantics
 *
 * Inserts an allocation operation into \p hStream.
 * A pointer to the allocated memory is returned immediately in *dptr.
 * The allocation must not be accessed until the the allocation operation completes.
 * The allocation comes from the memory pool associated with the stream's device.
 *
 * \note The default memory pool of a device contains device memory from that device.
 * \note Basic stream ordering allows future work submitted into the same stream to use the allocation.
 *       Stream query, stream synchronize, and CUDA events can be used to guarantee that the allocation
 *       operation completes before work submitted in a separate stream runs.
 * \note During stream capture, this function results in the creation of an allocation node.  In this case,
 *       the allocation is owned by the graph instead of the memory pool. The memory pool's properties
 *       are used to set the node's creation parameters.
 *
 * \param[out] devPtr  - Returned device pointer
 * \param[in] size     - Number of bytes to allocate
 * \param[in] hStream  - The stream establishing the stream ordering contract and the memory pool to allocate from
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported,
 * ::cudaErrorOutOfMemory,
 * \notefnerr
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cuMemAllocAsync,
 * \ref ::cudaMallocAsync(void** ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream)  "cudaMallocAsync (C++ API)", 
 * ::cudaMallocFromPoolAsync, ::cudaFreeAsync, ::cudaDeviceSetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolSetAccess, ::cudaMemPoolSetAttribute, ::cudaMemPoolGetAttribute
 */
extern __host__ cudaError_t CUDARTAPI cudaMallocAsync(void **devPtr, size_t size, cudaStream_t hStream);

/**
 * \brief Frees memory with stream ordered semantics
 *
 * Inserts a free operation into \p hStream.
 * The allocation must not be accessed after stream execution reaches the free.
 * After this API returns, accessing the memory from any subsequent work launched on the GPU
 * or querying its pointer attributes results in undefined behavior.
 *
 * \note During stream capture, this function results in the creation of a free node and
 *       must therefore be passed the address of a graph allocation.
 *
 * \param dptr - memory to free
 * \param hStream - The stream establishing the stream ordering promise
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \notefnerr
 * \note_null_stream
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cuMemFreeAsync, ::cudaMallocAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaFreeAsync(void *devPtr, cudaStream_t hStream);

/**
 * \brief Tries to release memory back to the OS
 *
 * Releases memory back to the OS until the pool contains fewer than minBytesToKeep
 * reserved bytes, or there is no more memory that the allocator can safely release.
 * The allocator cannot release OS allocations that back outstanding asynchronous allocations.
 * The OS allocations may happen at different granularity from the user allocations.
 *
 * \note: Allocations that have not been freed count as outstanding.
 * \note: Allocations that have been asynchronously freed but whose completion has
 *        not been observed on the host (eg. by a synchronize) can count as outstanding.
 *
 * \param[in] pool           - The memory pool to trim
 * \param[in] minBytesToKeep - If the pool has less than minBytesToKeep reserved,
 * the TrimTo operation is a no-op.  Otherwise the pool will be guaranteed to have
 * at least minBytesToKeep bytes reserved after the operation.
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_callback
 *
 * \sa ::cuMemPoolTrimTo, ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolTrimTo(cudaMemPool_t memPool, size_t minBytesToKeep);

/**
 * \brief Sets attributes of a memory pool
 *
 * Supported attributes are:
 * - ::cudaMemPoolAttrReleaseThreshold: (value type = cuuint64_t)
 *                    Amount of reserved memory in bytes to hold onto before trying
 *                    to release memory back to the OS. When more than the release
 *                    threshold bytes of memory are held by the memory pool, the
 *                    allocator will try to release memory back to the OS on the
 *                    next call to stream, event or context synchronize. (default 0)
 * - ::cudaMemPoolReuseFollowEventDependencies: (value type = int)
 *                    Allow ::cudaMallocAsync to use memory asynchronously freed
 *                    in another stream as long as a stream ordering dependency
 *                    of the allocating stream on the free action exists.
 *                    Cuda events and null stream interactions can create the required
 *                    stream ordered dependencies. (default enabled)
 * - ::cudaMemPoolReuseAllowOpportunistic: (value type = int)
 *                    Allow reuse of already completed frees when there is no dependency
 *                    between the free and allocation. (default enabled)
 * - ::cudaMemPoolReuseAllowInternalDependencies: (value type = int)
 *                    Allow ::cudaMallocAsync to insert new stream dependencies
 *                    in order to establish the stream ordering required to reuse
 *                    a piece of memory released by ::cudaFreeAsync (default enabled).
 * - ::cudaMemPoolAttrReservedMemHigh: (value type = cuuint64_t)
 *                    Reset the high watermark that tracks the amount of backing memory that was
 *                    allocated for the memory pool. It is illegal to set this attribute to a non-zero value.
 * - ::cudaMemPoolAttrUsedMemHigh: (value type = cuuint64_t)
 *                    Reset the high watermark that tracks the amount of used memory that was
 *                    allocated for the memory pool. It is illegal to set this attribute to a non-zero value.
 *
 * \param[in] pool  - The memory pool to modify
 * \param[in] attr  - The attribute to modify
 * \param[in] value - Pointer to the value to assign
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_callback
 *
 * \sa ::cuMemPoolSetAttribute, ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate

 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolSetAttribute(cudaMemPool_t memPool, enum cudaMemPoolAttr attr, void *value );

/**
 * \brief Gets attributes of a memory pool
 *
 * Supported attributes are:
 * - ::cudaMemPoolAttrReleaseThreshold: (value type = cuuint64_t)
 *                    Amount of reserved memory in bytes to hold onto before trying
 *                    to release memory back to the OS. When more than the release
 *                    threshold bytes of memory are held by the memory pool, the
 *                    allocator will try to release memory back to the OS on the
 *                    next call to stream, event or context synchronize. (default 0)
 * - ::cudaMemPoolReuseFollowEventDependencies: (value type = int)
 *                    Allow ::cudaMallocAsync to use memory asynchronously freed
 *                    in another stream as long as a stream ordering dependency
 *                    of the allocating stream on the free action exists.
 *                    Cuda events and null stream interactions can create the required
 *                    stream ordered dependencies. (default enabled)
 * - ::cudaMemPoolReuseAllowOpportunistic: (value type = int)
 *                    Allow reuse of already completed frees when there is no dependency
 *                    between the free and allocation. (default enabled)
 * - ::cudaMemPoolReuseAllowInternalDependencies: (value type = int)
 *                    Allow ::cudaMallocAsync to insert new stream dependencies
 *                    in order to establish the stream ordering required to reuse
 *                    a piece of memory released by ::cudaFreeAsync (default enabled).
 * - ::cudaMemPoolAttrReservedMemCurrent: (value type = cuuint64_t)
 *                    Amount of backing memory currently allocated for the mempool.
 * - ::cudaMemPoolAttrReservedMemHigh: (value type = cuuint64_t)
 *                    High watermark of backing memory allocated for the mempool since
 *                    the last time it was reset.
 * - ::cudaMemPoolAttrUsedMemCurrent: (value type = cuuint64_t)
 *                    Amount of memory from the pool that is currently in use by the application.
 * - ::cudaMemPoolAttrUsedMemHigh: (value type = cuuint64_t)
 *                    High watermark of the amount of memory from the pool that was in use by the
 *                    application since the last time it was reset.
 *
 * The following properties can be also be queried on imported and default pools:
 * - ::cudaMemPoolAttrAllocationType: (value type = cudaMemAllocationType)
 *                    The allocation type of the mempool
 * - ::cudaMemPoolAttrExportHandleTypes: (value type = cudaMemAllocationHandleType)
 *                    Available export handle types for the mempool. For imported pools this
 *                    value is always cudaMemHandleTypeNone as an imported pool cannot be
 *                    re-exported
 * - ::cudaMemPoolAttrLocationId: (value type = int)
 *                    The location id for the mempool. If the location type for this pool is
 *                    cudaMemLocationTypeInvisible then ID will be cudaInvalidDeviceId.
 * - ::cudaMemPoolAttrLocationType: (value type = cudaMemLocationType)
 *                    The location type for the mempool. For imported memory pools where the
 *                    device is not directly visible to the importing process or pools imported
 *                    via fabric handles across nodes this will be
 *                    cudaMemlocataionTypeInvisible.
 * - ::cudaMemPoolAttrMaxPoolSize: (value type = cuuint64_t)
 *                    Maximum size of the pool in bytes, this value may be higher than what was
 *                    initially passed to cuMemPoolCreate due to alignment requirements. A
 *                    value of 0 indicates no maximum size. For cudaMemAllocationTypeManaged
 *                    and IPC imported pools this value will be system dependent.
 * - ::cudaMemPoolAttrHwDecompressEnabled: (value type = int)
 *                    Indicates whether the pool has hardware compresssion enabled
 *
 * \param[in] pool  - The memory pool to get attributes of
 * \param[in] attr  - The attribute to get
 * \param[in] value - Retrieved value
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_callback
 *
 * \sa ::cuMemPoolGetAttribute, ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate

 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolGetAttribute(cudaMemPool_t memPool, enum cudaMemPoolAttr attr, void *value );

/**
 * \brief Controls visibility of pools between devices
 *
 * \param[in] pool  - The pool being modified
 * \param[in] map   - Array of access descriptors. Each descriptor instructs the access to enable for a single gpu
 * \param[in] count - Number of descriptors in the map array.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa ::cuMemPoolSetAccess, ::cudaMemPoolGetAccess, ::cudaMallocAsync, cudaFreeAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolSetAccess(cudaMemPool_t memPool, const struct cudaMemAccessDesc *descList, size_t count);

/**
 * \brief Returns the accessibility of a pool from a device
 *
 * Returns the accessibility of the pool's memory from the specified location.
 *
 * \param[out] flags   - the accessibility of the pool from the specified location
 * \param[in] memPool  - the pool being queried
 * \param[in] location - the location accessing the pool
 *
 * \sa ::cuMemPoolGetAccess, ::cudaMemPoolSetAccess
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolGetAccess(enum cudaMemAccessFlags *flags, cudaMemPool_t memPool, struct cudaMemLocation *location);

/**
 * \brief Creates a memory pool
 *
 * Creates a CUDA memory pool and returns the handle in \p pool.  The \p poolProps determines
 * the properties of the pool such as the backing device and IPC capabilities.
 *
 * To create a memory pool for host memory not targeting a specific NUMA node, applications must set
 * set ::cudaMemPoolProps::cudaMemLocation::type to ::cudaMemLocationTypeHost.
 * ::cudaMemPoolProps::cudaMemLocation::id is ignored for such pools.
 * Pools created with the type ::cudaMemLocationTypeHost are not IPC capable and
 * ::cudaMemPoolProps::handleTypes must be 0, any other values will result in
 * ::cudaErrorInvalidValue.
 * To create a memory pool targeting a specific host NUMA node, applications must
 * set ::cudaMemPoolProps::cudaMemLocation::type to ::cudaMemLocationTypeHostNuma and
 * ::cudaMemPoolProps::cudaMemLocation::id must specify the NUMA ID of the host memory node.
 * Specifying ::cudaMemLocationTypeHostNumaCurrent as the
 * ::cudaMemPoolProps::cudaMemLocation::type will result in ::cudaErrorInvalidValue.
* By default, the pool's memory will be accessible from the device it is allocated on.
 * In the case of pools created with ::cudaMemLocationTypeHostNuma or
 * ::cudaMemLocationTypeHost, their default accessibility will be from the host
 * CPU.
 * Applications can control the maximum size of the pool by specifying a non-zero value for ::cudaMemPoolProps::maxSize.
 * If set to 0, the maximum size of the pool will default to a system dependent value.
 *
 * Applications that intend to use ::CU_MEM_HANDLE_TYPE_FABRIC based memory sharing must ensure:
 * (1) `nvidia-caps-imex-channels` character device is created by the driver and is listed under /proc/devices 
 * (2) have at least one IMEX channel file accessible by the user launching the application.
 *
 * When exporter and importer CUDA processes have been granted access to the same IMEX channel, they can securely
 * share memory.
 *
 * The IMEX channel security model works on a per user basis. Which means all processes under a user can share
 * memory if the user has access to a valid IMEX channel. When multi-user isolation is desired, a separate IMEX
 * channel is required for each user.
 *
 * These channel files exist in /dev/nvidia-caps-imex-channels/channel* and can be created using standard OS
 * native calls like mknod on Linux. For example: To create channel0 with the major number from /proc/devices
 * users can execute the following command: `mknod /dev/nvidia-caps-imex-channels/channel0 c <major number> 0`
 *
 * To create a managed memory pool, applications must set ::cudaMemPoolProps:cudaMemAllocationType to ::cudaMemAllocationTypeManaged.
 * ::cudaMemPoolProps::cudaMemAllocationHandleType must also be set to ::cudaMemHandleTypeNone since IPC is not supported.
 * For managed memory pools, ::cudaMemPoolProps::cudaMemLocation will be treated as the preferred location for all allocations created from the pool.
 * An application can also set ::cudaMemLocationTypeNone to indicate no preferred location.
 * ::cudaMemPoolProps::maxSize must be set to zero for managed memory pools. 
 * ::cudaMemPoolProps::usage should be zero as decompress for managed memory is not supported.
 * For managed memory pools, all devices on the system must have non-zero ::concurrentManagedAccess. If not, this call returns ::cudaErrorNotSupported
 *
 * \note Specifying ::cudaMemHandleTypeNone creates a memory pool that will not support IPC.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 *
 * \sa ::cuMemPoolCreate, ::cudaDeviceSetMemPool, ::cudaMallocFromPoolAsync, ::cudaMemPoolExportToShareableHandle, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool

 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolCreate(cudaMemPool_t *memPool, const struct cudaMemPoolProps *poolProps);

/**
 * \brief Destroys the specified memory pool 
 *
 * If any pointers obtained from this pool haven't been freed or
 * the pool has free operations that haven't completed
 * when ::cudaMemPoolDestroy is invoked, the function will return immediately and the
 * resources associated with the pool will be released automatically
 * once there are no more outstanding allocations.
 *
 * Destroying the current mempool of a device sets the default mempool of
 * that device as the current mempool for that device.
 *
 * \note A device's default memory pool cannot be destroyed.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa cuMemPoolDestroy, ::cudaFreeAsync, ::cudaDeviceSetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolDestroy(cudaMemPool_t memPool);

/**
 * \brief Returns the default memory pool for a given location and allocation type 
 *
 * The memory location can be of one of ::cudaMemLocationTypeDevice, ::cudaMemLocationTypeHost or
 * ::cudaMemLocationTypeHostNuma. The allocation type can be one of ::cudaMemAllocationTypePinned or
 * ::cudaMemAllocationTypeManaged. When the allocation type is ::cudaMemAllocationTypeManaged,
 * the location type can also be ::cudaMemLocationTypeNone to indicate no preferred location
 * for the managed memory pool. In all other cases, the call return ::cudaErrorInvalidValue
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported,
 *
 * \sa ::cuMemAllocAsync, ::cuMemPoolTrimTo, ::cuMemPoolGetAttribute, ::cuMemPoolSetAttribute, cuMemPoolSetAccess, ::cuMemGetMemPool, ::cuMemPoolCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaMemGetDefaultMemPool(cudaMemPool_t *memPool, struct cudaMemLocation *location, enum cudaMemAllocationType type);

/**
 * \brief Gets the current memory pool for a given memory location and allocation type
 * 
 * The memory location can be of one of ::cudaMemLocationTypeDevice, ::cudaMemLocationTypeHost or
 * ::cudaMemLocationTypeHostNuma. The allocation type can be one of ::cudaMemAllocationTypePinned or 
 * ::cudaMemAllocationTypeManaged. When the allocation type is ::cudaMemAllocationTypeManaged, 
 * the location type can also be ::cudaMemLocationTypeNone to indicate no preferred location
 * for the managed memory pool. In all other cases, the call return ::cudaErrorInvalidValue
 *
 * Returns the last pool provided to ::cudaMemSetMemPool or ::cudaDeviceSetMemPool for this location and allocation type
 * or the location's default memory pool if ::cudaMemSetMemPool or ::cudaDeviceSetMemPool for that allocType and location 
 * has never been called. 
 * By default the current mempool of a location is the default mempool for a device that can be obtained via cudaMemGetDefaultMemPool
 * Otherwise the returned pool must have been set with ::cudaDeviceSetMemPool.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa ::cuDeviceGetDefaultMemPool, ::cuMemPoolCreate, ::cuDeviceSetMemPool, ::cuMemSetMemPool
 */
extern __host__ cudaError_t CUDARTAPI cudaMemGetMemPool(cudaMemPool_t *memPool, struct cudaMemLocation *location, enum cudaMemAllocationType type);

/**
 * \brief Sets the current memory pool for a memory location and allocation type
 *
 * The memory location can be of one of ::cudaMemLocationTypeDevice, ::cudaMemLocationTypeHost or
 * ::cudaMemLocationTypeHostNuma. The allocation type can be one of ::cudaMemAllocationTypePinned or 
 * ::cudaMemAllocationTypeManaged. When the allocation type is ::cudaMemAllocationTypeManaged, 
 * the location type can also be ::cudaMemLocationTypeNone to indicate no preferred location
 * for the managed memory pool. In all other cases, the call return ::cudaErrorInvalidValue
 *
 * When a memory pool is set as the current memory pool, the location parameter should be the same as the location of the pool.
 * If the location type or index don't match, the call returns ::cudaErrorInvalidValue.
 * The type of memory pool should also match the parameter allocType. Else the call returns ::cudaErrorInvalidValue.  
 * By default, a memory location's current memory pool is its default memory pool.
 * If the location type is ::cudaMemLocationTypeDevice and the allocation type is ::cudaMemAllocationTypePinned, then 
 * this API is the equivalent of calling ::cudaDeviceSetMemPool with the location id as the device. 
 * For further details on the implications, please refer to the documentation for ::cudaDeviceSetMemPool.
 * 
 * \note Use ::cudaMallocFromPoolAsync to specify asynchronous allocations from a device different
 * than the one the stream runs on.
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa ::cuDeviceGetDefaultMemPool, ::cuDeviceGetMemPool, ::cuMemGetMemPool, ::cuMemPoolCreate, ::cuMemPoolDestroy, ::cuMemAllocFromPoolAsync
 */
extern __host__ cudaError_t CUDARTAPI cudaMemSetMemPool(struct cudaMemLocation *location, enum cudaMemAllocationType type, cudaMemPool_t memPool);

/**
 * \brief Allocates memory from a specified pool with stream ordered semantics.
 *
 * Inserts an allocation operation into \p hStream.
 * A pointer to the allocated memory is returned immediately in *dptr.
 * The allocation must not be accessed until the the allocation operation completes.
 * The allocation comes from the specified memory pool.
 *
 * \note
 *    -  The specified memory pool may be from a device different than that of the specified \p hStream.
 *
 *    -  Basic stream ordering allows future work submitted into the same stream to use the allocation.
 *       Stream query, stream synchronize, and CUDA events can be used to guarantee that the allocation
 *       operation completes before work submitted in a separate stream runs.
 *
 * \note During stream capture, this function results in the creation of an allocation node.  In this case,
 *       the allocation is owned by the graph instead of the memory pool. The memory pool's properties
 *       are used to set the node's creation parameters.
 *
 * \param[out] ptr     - Returned device pointer
 * \param[in] bytesize - Number of bytes to allocate
 * \param[in] memPool  - The pool to allocate from
 * \param[in] stream   - The stream establishing the stream ordering semantic
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported,
 * ::cudaErrorOutOfMemory
 *
 * \sa ::cuMemAllocFromPoolAsync,
 * \ref ::cudaMallocAsync(void** ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream)  "cudaMallocAsync (C++ API)", 
 * ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaMemPoolCreate, ::cudaMemPoolSetAccess, ::cudaMemPoolSetAttribute
 */
extern __host__ cudaError_t CUDARTAPI cudaMallocFromPoolAsync(void **ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream);

/**
 * \brief Exports a memory pool to the requested handle type.
 *
 * Given an IPC capable mempool, create an OS handle to share the pool with another process.
 * A recipient process can convert the shareable handle into a mempool with ::cudaMemPoolImportFromShareableHandle.
 * Individual pointers can then be shared with the ::cudaMemPoolExportPointer and ::cudaMemPoolImportPointer APIs.
 * The implementation of what the shareable handle is and how it can be transferred is defined by the requested
 * handle type.
 *
 * \note: To create an IPC capable mempool, create a mempool with a CUmemAllocationHandleType other than cudaMemHandleTypeNone.
 *
 * \param[out] handle_out  - pointer to the location in which to store the requested handle 
 * \param[in] pool         - pool to export
 * \param[in] handleType   - the type of handle to create
 * \param[in] flags        - must be 0
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorOutOfMemory
 *
 * \sa ::cuMemPoolExportToShareableHandle, ::cudaMemPoolImportFromShareableHandle, ::cudaMemPoolExportPointer, ::cudaMemPoolImportPointer
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolExportToShareableHandle(
    void                            *shareableHandle,
    cudaMemPool_t                    memPool,
    enum cudaMemAllocationHandleType handleType,
    unsigned int                     flags);

/**
 * \brief imports a memory pool from a shared handle.
 *
 * Specific allocations can be imported from the imported pool with ::cudaMemPoolImportPointer.
 *
 * \note Imported memory pools do not support creating new allocations.
 *       As such imported memory pools may not be used in ::cudaDeviceSetMemPool
 *       or ::cudaMallocFromPoolAsync calls.
 *
 * \param[out] pool_out    - Returned memory pool
 * \param[in] handle       - OS handle of the pool to open
 * \param[in] handleType   - The type of handle being imported
 * \param[in] flags        - must be 0
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorOutOfMemory
 *
 * \sa ::cuMemPoolImportFromShareableHandle, ::cudaMemPoolExportToShareableHandle, ::cudaMemPoolExportPointer, ::cudaMemPoolImportPointer
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolImportFromShareableHandle(
    cudaMemPool_t                   *memPool,
    void                            *shareableHandle,
    enum cudaMemAllocationHandleType handleType,
    unsigned int                     flags);

/**
 * \brief Export data to share a memory pool allocation between processes.
 *
 * Constructs \p shareData_out for sharing a specific allocation from an already shared memory pool.
 * The recipient process can import the allocation with the ::cudaMemPoolImportPointer api.
 * The data is not a handle and may be shared through any IPC mechanism.
 *
 * \param[out] shareData_out - Returned export data
 * \param[in] ptr            - pointer to memory being exported
 *
 * \returns
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorOutOfMemory
 *
 * \sa ::cuMemPoolExportPointer, ::cudaMemPoolExportToShareableHandle, ::cudaMemPoolImportFromShareableHandle, ::cudaMemPoolImportPointer
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolExportPointer(struct cudaMemPoolPtrExportData *exportData, void *ptr);

/**
 * \brief Import a memory pool allocation from another process.
 *
 * Returns in \p ptr_out a pointer to the imported memory.
 * The imported memory must not be accessed before the allocation operation completes
 * in the exporting process. The imported memory must be freed from all importing processes before
 * being freed in the exporting process. The pointer may be freed with cudaFree
 * or cudaFreeAsync.  If ::cudaFreeAsync is used, the free must be completed
 * on the importing process before the free operation on the exporting process.
 *
 * \note The ::cudaFreeAsync api may be used in the exporting process before
 *       the ::cudaFreeAsync operation completes in its stream as long as the
 *       ::cudaFreeAsync in the exporting process specifies a stream with
 *       a stream dependency on the importing process's ::cudaFreeAsync.
 *
 * \param[out] ptr_out  - pointer to imported memory
 * \param[in] pool      - pool from which to import
 * \param[in] shareData - data specifying the memory to import
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemPoolImportPointer, ::cudaMemPoolExportToShareableHandle, ::cudaMemPoolImportFromShareableHandle, ::cudaMemPoolExportPointer
 */
extern __host__ cudaError_t CUDARTAPI cudaMemPoolImportPointer(void **ptr, cudaMemPool_t memPool, struct cudaMemPoolPtrExportData *exportData);

/** @} */ /* END CUDART_MEMORY_POOLS */

/**
 * \defgroup CUDART_UNIFIED Unified Addressing
 *
 * ___MANBRIEF___ unified addressing functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the unified addressing functions of the CUDA 
 * runtime application programming interface.
 *
 * @{
 *
 * \section CUDART_UNIFIED_overview Overview
 *
 * CUDA devices can share a unified address space with the host.  
 * For these devices there is no distinction between a device
 * pointer and a host pointer -- the same pointer value may be 
 * used to access memory from the host program and from a kernel 
 * running on the device (with exceptions enumerated below).
 *
 * \section CUDART_UNIFIED_support Supported Platforms
 * 
 * Whether or not a device supports unified addressing may be 
 * queried by calling ::cudaGetDeviceProperties() with the device 
 * property ::cudaDeviceProp::unifiedAddressing.
 *
 * Unified addressing is automatically enabled in 64-bit processes .
 *
 * \section CUDART_UNIFIED_lookup Looking Up Information from Pointer Values
 *
 * It is possible to look up information about the memory which backs a 
 * pointer value.  For instance, one may want to know if a pointer points
 * to host or device memory.  As another example, in the case of device 
 * memory, one may want to know on which CUDA device the memory 
 * resides.  These properties may be queried using the function 
 * ::cudaPointerGetAttributes()
 *
 * Since pointers are unique, it is not necessary to specify information
 * about the pointers specified to ::cudaMemcpy() and other copy functions.  
 * The copy direction ::cudaMemcpyDefault may be used to specify that the 
 * CUDA runtime should infer the location of the pointer from its value.
 *
 * \section CUDART_UNIFIED_automaphost Automatic Mapping of Host Allocated Host Memory
 *
 * All host memory allocated through all devices using ::cudaMallocHost() and
 * ::cudaHostAlloc() is always directly accessible from all devices that 
 * support unified addressing.  This is the case regardless of whether or 
 * not the flags ::cudaHostAllocPortable and ::cudaHostAllocMapped are 
 * specified.
 *
 * The pointer value through which allocated host memory may be accessed 
 * in kernels on all devices that support unified addressing is the same 
 * as the pointer value through which that memory is accessed on the host.
 * It is not necessary to call ::cudaHostGetDevicePointer() to get the device 
 * pointer for these allocations.  
 *
 * Note that this is not the case for memory allocated using the flag
 * ::cudaHostAllocWriteCombined, as discussed below.
 *
 * \section CUDART_UNIFIED_autopeerregister Direct Access of Peer Memory
 
 * Upon enabling direct access from a device that supports unified addressing 
 * to another peer device that supports unified addressing using 
 * ::cudaDeviceEnablePeerAccess() all memory allocated in the peer device using 
 * ::cudaMalloc() and ::cudaMallocPitch() will immediately be accessible 
 * by the current device.  The device pointer value through 
 * which any peer's memory may be accessed in the current device 
 * is the same pointer value through which that memory may be 
 * accessed from the peer device. 
 *
 * \section CUDART_UNIFIED_exceptions Exceptions, Disjoint Addressing
 * 
 * Not all memory may be accessed on devices through the same pointer
 * value through which they are accessed on the host.  These exceptions
 * are host memory registered using ::cudaHostRegister() and host memory
 * allocated using the flag ::cudaHostAllocWriteCombined.  For these 
 * exceptions, there exists a distinct host and device address for the
 * memory.  The device address is guaranteed to not overlap any valid host
 * pointer range and is guaranteed to have the same value across all devices
 * that support unified addressing.  
 * 
 * This device address may be queried using ::cudaHostGetDevicePointer() 
 * when a device using unified addressing is current.  Either the host 
 * or the unified device pointer value may be used to refer to this memory 
 * in ::cudaMemcpy() and similar functions using the ::cudaMemcpyDefault 
 * memory direction.
 *
 */

/**
 * \brief Returns attributes about a specified pointer
 *
 * Returns in \p *attributes the attributes of the pointer \p ptr.
 * If pointer was not allocated in, mapped by or registered with context
 * supporting unified addressing ::cudaErrorInvalidValue is returned.
 *
 * \note In CUDA 11.0 forward passing host pointer will return ::cudaMemoryTypeUnregistered
 * in ::cudaPointerAttributes::type and call will return ::cudaSuccess.
 *
 * The ::cudaPointerAttributes structure is defined as:
 * \code
    struct cudaPointerAttributes {
        enum cudaMemoryType type;
        int device;
        void *devicePointer;
        void *hostPointer;
    }
    \endcode
 * In this structure, the individual fields mean
 *
 * - \ref ::cudaPointerAttributes::type identifies type of memory. It can be
 *    ::cudaMemoryTypeUnregistered for unregistered host memory,
 *    ::cudaMemoryTypeHost for registered host memory, ::cudaMemoryTypeDevice for device
 *    memory or  ::cudaMemoryTypeManaged for managed memory.
 *
 * - \ref ::cudaPointerAttributes::device "device" is the device against which
 *   \p ptr was allocated.  If \p ptr has memory type ::cudaMemoryTypeDevice
 *   then this identifies the device on which the memory referred to by \p ptr
 *   physically resides.  If \p ptr has memory type ::cudaMemoryTypeHost then this
 *   identifies the device which was current when the allocation was made
 *   (and if that device is deinitialized then this allocation will vanish
 *   with that device's state).
 *
 * - \ref ::cudaPointerAttributes::devicePointer "devicePointer" is
 *   the device pointer alias through which the memory referred to by \p ptr
 *   may be accessed on the current device.
 *   If the memory referred to by \p ptr cannot be accessed directly by the 
 *   current device then this is NULL.  
 *
 * - \ref ::cudaPointerAttributes::hostPointer "hostPointer" is
 *   the host pointer alias through which the memory referred to by \p ptr
 *   may be accessed on the host.
 *   If the memory referred to by \p ptr cannot be accessed directly by the
 *   host then this is NULL.
 *
 * \param attributes - Attributes for the specified pointer
 * \param ptr        - Pointer to get attributes for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice,
 * ::cudaChooseDevice,
 * ::cudaInitDevice,
 * ::cuPointerGetAttributes
 */
extern __host__ cudaError_t CUDARTAPI cudaPointerGetAttributes(struct cudaPointerAttributes *attributes, const void *ptr);

/** @} */ /* END CUDART_UNIFIED */

/**
 * \defgroup CUDART_PEER Peer Device Memory Access
 *
 * ___MANBRIEF___ peer device memory access functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the peer device memory access functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Queries if a device may directly access a peer device's memory.
 *
 * Returns in \p *canAccessPeer a value of 1 if device \p device is capable of
 * directly accessing memory from \p peerDevice and 0 otherwise.  If direct
 * access of \p peerDevice from \p device is possible, then access may be
 * enabled by calling ::cudaDeviceEnablePeerAccess().
 *
 * \param canAccessPeer - Returned access capability
 * \param device        - Device from which allocations on \p peerDevice are to
 *                        be directly accessed.
 * \param peerDevice    - Device on which the allocations to be directly accessed 
 *                        by \p device reside.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceEnablePeerAccess,
 * ::cudaDeviceDisablePeerAccess,
 * ::cuDeviceCanAccessPeer
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceCanAccessPeer(int *canAccessPeer, int device, int peerDevice);

/**
 * \brief Enables direct access to memory allocations on a peer device.
 *
 * On success, all allocations from \p peerDevice will immediately be accessible by
 * the current device.  They will remain accessible until access is explicitly
 * disabled using ::cudaDeviceDisablePeerAccess() or either device is reset using
 * ::cudaDeviceReset().
 *
 * Note that access granted by this call is unidirectional and that in order to access
 * memory on the current device from \p peerDevice, a separate symmetric call 
 * to ::cudaDeviceEnablePeerAccess() is required.
 *
 * Note that there are both device-wide and system-wide limitations per system
 * configuration, as noted in the CUDA Programming Guide under the section
 * "Peer-to-Peer Memory Access".
 *
 * Returns ::cudaErrorInvalidDevice if ::cudaDeviceCanAccessPeer() indicates
 * that the current device cannot directly access memory from \p peerDevice.
 *
 * Returns ::cudaErrorPeerAccessAlreadyEnabled if direct access of
 * \p peerDevice from the current device has already been enabled.
 *
 * Returns ::cudaErrorInvalidValue if \p flags is not 0.
 *
 * \param peerDevice  - Peer device to enable direct access to from the current device
 * \param flags       - Reserved for future use and must be set to 0
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorPeerAccessAlreadyEnabled,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceCanAccessPeer,
 * ::cudaDeviceDisablePeerAccess,
 * ::cuCtxEnablePeerAccess
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceEnablePeerAccess(int peerDevice, unsigned int flags);

/**
 * \brief Disables direct access to memory allocations on a peer device.
 *
 * Returns ::cudaErrorPeerAccessNotEnabled if direct access to memory on
 * \p peerDevice has not yet been enabled from the current device.
 *
 * \param peerDevice - Peer device to disable direct access to
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorPeerAccessNotEnabled,
 * ::cudaErrorInvalidDevice
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa ::cudaDeviceCanAccessPeer,
 * ::cudaDeviceEnablePeerAccess,
 * ::cuCtxDisablePeerAccess
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceDisablePeerAccess(int peerDevice);

/** @} */ /* END CUDART_PEER */

/** \defgroup CUDART_OPENGL OpenGL Interoperability */

/** \defgroup CUDART_OPENGL_DEPRECATED OpenGL Interoperability [DEPRECATED] */

/** \defgroup CUDART_D3D9 Direct3D 9 Interoperability */

/** \defgroup CUDART_D3D9_DEPRECATED Direct3D 9 Interoperability [DEPRECATED] */

/** \defgroup CUDART_D3D10 Direct3D 10 Interoperability */

/** \defgroup CUDART_D3D10_DEPRECATED Direct3D 10 Interoperability [DEPRECATED] */

/** \defgroup CUDART_D3D11 Direct3D 11 Interoperability */

/** \defgroup CUDART_D3D11_DEPRECATED Direct3D 11 Interoperability [DEPRECATED] */

/** \defgroup CUDART_VDPAU VDPAU Interoperability */

/** \defgroup CUDART_EGL EGL Interoperability */

/**
 * \defgroup CUDART_INTEROP Graphics Interoperability
 *
 * ___MANBRIEF___ graphics interoperability functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the graphics interoperability functions of the CUDA
 * runtime application programming interface.
 *
 * @{
 */

/**
 * \brief Unregisters a graphics resource for access by CUDA
 *
 * Unregisters the graphics resource \p resource so it is not accessible by
 * CUDA unless registered again.
 *
 * If \p resource is invalid then ::cudaErrorInvalidResourceHandle is
 * returned.
 *
 * \param resource - Resource to unregister
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa
 * ::cudaGraphicsD3D9RegisterResource,
 * ::cudaGraphicsD3D10RegisterResource,
 * ::cudaGraphicsD3D11RegisterResource,
 * ::cudaGraphicsGLRegisterBuffer,
 * ::cudaGraphicsGLRegisterImage,
 * ::cuGraphicsUnregisterResource
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsUnregisterResource(cudaGraphicsResource_t resource);

/**
 * \brief Set usage flags for mapping a graphics resource
 *
 * Set \p flags for mapping the graphics resource \p resource.
 *
 * Changes to \p flags will take effect the next time \p resource is mapped.
 * The \p flags argument may be any of the following:
 * - ::cudaGraphicsMapFlagsNone: Specifies no hints about how \p resource will
 *     be used. It is therefore assumed that CUDA may read from or write to \p resource.
 * - ::cudaGraphicsMapFlagsReadOnly: Specifies that CUDA will not write to \p resource.
 * - ::cudaGraphicsMapFlagsWriteDiscard: Specifies CUDA will not read from \p resource and will
 *   write over the entire contents of \p resource, so none of the data
 *   previously stored in \p resource will be preserved.
 *
 * If \p resource is presently mapped for access by CUDA then ::cudaErrorUnknown is returned.
 * If \p flags is not one of the above values then ::cudaErrorInvalidValue is returned.
 *
 * \param resource - Registered resource to set flags for
 * \param flags    - Parameters for resource mapping
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown,
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphicsMapResources,
 * ::cuGraphicsResourceSetMapFlags
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceSetMapFlags(cudaGraphicsResource_t resource, unsigned int flags);

/**
 * \brief Map graphics resources for access by CUDA
 *
 * Maps the \p count graphics resources in \p resources for access by CUDA.
 *
 * The resources in \p resources may be accessed by CUDA until they
 * are unmapped. The graphics API from which \p resources were registered
 * should not access any resources while they are mapped by CUDA. If an
 * application does so, the results are undefined.
 *
 * This function provides the synchronization guarantee that any graphics calls
 * issued before ::cudaGraphicsMapResources() will complete before any subsequent CUDA
 * work issued in \p stream begins.
 *
 * If \p resources contains any duplicate entries then ::cudaErrorInvalidResourceHandle
 * is returned. If any of \p resources are presently mapped for access by
 * CUDA then ::cudaErrorUnknown is returned.
 *
 * \param count     - Number of resources to map
 * \param resources - Resources to map for CUDA
 * \param stream    - Stream for synchronization
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphicsResourceGetMappedPointer,
 * ::cudaGraphicsSubResourceGetMappedArray,
 * ::cudaGraphicsUnmapResources,
 * ::cuGraphicsMapResources
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsMapResources(int count, cudaGraphicsResource_t *resources, cudaStream_t stream __dv(0));

/**
 * \brief Unmap graphics resources.
 *
 * Unmaps the \p count graphics resources in \p resources.
 *
 * Once unmapped, the resources in \p resources may not be accessed by CUDA
 * until they are mapped again.
 *
 * This function provides the synchronization guarantee that any CUDA work issued
 * in \p stream before ::cudaGraphicsUnmapResources() will complete before any
 * subsequently issued graphics work begins.
 *
 * If \p resources contains any duplicate entries then ::cudaErrorInvalidResourceHandle
 * is returned. If any of \p resources are not presently mapped for access by
 * CUDA then ::cudaErrorUnknown is returned.
 *
 * \param count     - Number of resources to unmap
 * \param resources - Resources to unmap
 * \param stream    - Stream for synchronization
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown
 * \note_null_stream
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphicsMapResources,
 * ::cuGraphicsUnmapResources
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsUnmapResources(int count, cudaGraphicsResource_t *resources, cudaStream_t stream __dv(0));

/**
 * \brief Get an device pointer through which to access a mapped graphics resource.
 *
 * Returns in \p *devPtr a pointer through which the mapped graphics resource
 * \p resource may be accessed.
 * Returns in \p *size the size of the memory in bytes which may be accessed from that pointer.
 * The value set in \p devPtr may change every time that \p resource is mapped.
 *
 * If \p resource is not a buffer then it cannot be accessed via a pointer and
 * ::cudaErrorUnknown is returned.
 * If \p resource is not mapped then ::cudaErrorUnknown is returned.
 * *
 * \param devPtr     - Returned pointer through which \p resource may be accessed
 * \param size       - Returned size of the buffer accessible starting at \p *devPtr
 * \param resource   - Mapped resource to access
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphicsMapResources,
 * ::cudaGraphicsSubResourceGetMappedArray,
 * ::cuGraphicsResourceGetMappedPointer
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceGetMappedPointer(void **devPtr, size_t *size, cudaGraphicsResource_t resource);

/**
 * \brief Get an array through which to access a subresource of a mapped graphics resource.
 *
 * Returns in \p *array an array through which the subresource of the mapped
 * graphics resource \p resource which corresponds to array index \p arrayIndex
 * and mipmap level \p mipLevel may be accessed.  The value set in \p array may
 * change every time that \p resource is mapped.
 *
 * If \p resource is not a texture then it cannot be accessed via an array and
 * ::cudaErrorUnknown is returned.
 * If \p arrayIndex is not a valid array index for \p resource then
 * ::cudaErrorInvalidValue is returned.
 * If \p mipLevel is not a valid mipmap level for \p resource then
 * ::cudaErrorInvalidValue is returned.
 * If \p resource is not mapped then ::cudaErrorUnknown is returned.
 *
 * \param array       - Returned array through which a subresource of \p resource may be accessed
 * \param resource    - Mapped resource to access
 * \param arrayIndex  - Array index for array textures or cubemap face
 *                      index as defined by ::cudaGraphicsCubeFace for
 *                      cubemap textures for the subresource to access
 * \param mipLevel    - Mipmap level for the subresource to access
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphicsResourceGetMappedPointer,
 * ::cuGraphicsSubResourceGetMappedArray
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsSubResourceGetMappedArray(cudaArray_t *array, cudaGraphicsResource_t resource, unsigned int arrayIndex, unsigned int mipLevel);

/**
 * \brief Get a mipmapped array through which to access a mapped graphics resource.
 *
 * Returns in \p *mipmappedArray a mipmapped array through which the mapped
 * graphics resource \p resource may be accessed. The value set in \p mipmappedArray may
 * change every time that \p resource is mapped.
 *
 * If \p resource is not a texture then it cannot be accessed via an array and
 * ::cudaErrorUnknown is returned.
 * If \p resource is not mapped then ::cudaErrorUnknown is returned.
 *
 * \param mipmappedArray - Returned mipmapped array through which \p resource may be accessed
 * \param resource       - Mapped resource to access
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorUnknown
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphicsResourceGetMappedPointer,
 * ::cuGraphicsResourceGetMappedMipmappedArray
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceGetMappedMipmappedArray(cudaMipmappedArray_t *mipmappedArray, cudaGraphicsResource_t resource);

/** @} */ /* END CUDART_INTEROP */

/**
 * \defgroup CUDART_TEXTURE_OBJECT Texture Object Management
 *
 * ___MANBRIEF___ texture object management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the low level texture object management functions
 * of the CUDA runtime application programming interface. The texture
 * object API is only supported on devices of compute capability 3.0 or higher.
 *
 * @{
 */

/**
 * \brief Get the channel descriptor of an array
 *
 * Returns in \p *desc the channel descriptor of the CUDA array \p array.
 *
 * \param desc  - Channel format
 * \param array - Memory array on device
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa \ref ::cudaCreateChannelDesc(int, int, int, int, cudaChannelFormatKind) "cudaCreateChannelDesc (C API)",
 * ::cudaCreateTextureObject, ::cudaCreateSurfaceObject
 */
extern __host__ cudaError_t CUDARTAPI cudaGetChannelDesc(struct cudaChannelFormatDesc *desc, cudaArray_const_t array);

/**
 * \brief Returns a channel descriptor using the specified format
 *
 * Returns a channel descriptor with format \p f and number of bits of each
 * component \p x, \p y, \p z, and \p w.  The ::cudaChannelFormatDesc is
 * defined as:
 * \code
  struct cudaChannelFormatDesc {
    int x, y, z, w;
    enum cudaChannelFormatKind f;
  };
 * \endcode
 *
 * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned,
 * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat.
 *
 * \param x - X component
 * \param y - Y component
 * \param z - Z component
 * \param w - W component
 * \param f - Channel format
 *
 * \return
 * Channel descriptor with format \p f
 *
 * \sa \ref ::cudaCreateChannelDesc(void) "cudaCreateChannelDesc (C++ API)",
 * ::cudaGetChannelDesc, ::cudaCreateTextureObject, ::cudaCreateSurfaceObject
 */
extern __host__ struct cudaChannelFormatDesc CUDARTAPI cudaCreateChannelDesc(int x, int y, int z, int w, enum cudaChannelFormatKind f);

/**
 * \brief Creates a texture object
 *
 * Creates a texture object and returns it in \p pTexObject. \p pResDesc describes
 * the data to texture from. \p pTexDesc describes how the data should be sampled.
 * \p pResViewDesc is an optional argument that specifies an alternate format for
 * the data described by \p pResDesc, and also describes the subresource region
 * to restrict access to when texturing. \p pResViewDesc can only be specified if
 * the type of resource is a CUDA array or a CUDA mipmapped array not in a block
 * compressed format.
 *
 * Texture objects are only supported on devices of compute capability 3.0 or higher.
 * Additionally, a texture object is an opaque value, and, as such, should only be
 * accessed through CUDA API calls.
 *
 * The ::cudaResourceDesc structure is defined as:
 * \code
        struct cudaResourceDesc {
            enum cudaResourceType resType;
            
            union {
                struct {
                    cudaArray_t array;
                } array;
                struct {
                    cudaMipmappedArray_t mipmap;
                } mipmap;
                struct {
                    void *devPtr;
                    struct cudaChannelFormatDesc desc;
                    size_t sizeInBytes;
                } linear;
                struct {
                    void *devPtr;
                    struct cudaChannelFormatDesc desc;
                    size_t width;
                    size_t height;
                    size_t pitchInBytes;
                } pitch2D;
            } res;
        };
 * \endcode
 * where:
 * - ::cudaResourceDesc::resType specifies the type of resource to texture from.
 * CUresourceType is defined as:
 * \code
        enum cudaResourceType {
            cudaResourceTypeArray          = 0x00,
            cudaResourceTypeMipmappedArray = 0x01,
            cudaResourceTypeLinear         = 0x02,
            cudaResourceTypePitch2D        = 0x03
        };
 * \endcode
 *
 * \par
 * If ::cudaResourceDesc::resType is set to ::cudaResourceTypeArray, ::cudaResourceDesc::res::array::array
 * must be set to a valid CUDA array handle.
 *
 * \par
 * If ::cudaResourceDesc::resType is set to ::cudaResourceTypeMipmappedArray, ::cudaResourceDesc::res::mipmap::mipmap
 * must be set to a valid CUDA mipmapped array handle and ::cudaTextureDesc::normalizedCoords must be set to true.
 *
 * \par
 * If ::cudaResourceDesc::resType is set to ::cudaResourceTypeLinear, ::cudaResourceDesc::res::linear::devPtr
 * must be set to a valid device pointer, that is aligned to ::cudaDeviceProp::textureAlignment.
 * ::cudaResourceDesc::res::linear::desc describes the format and the number of components per array element. ::cudaResourceDesc::res::linear::sizeInBytes
 * specifies the size of the array in bytes. The total number of elements in the linear address range cannot exceed 
 * ::cudaDeviceGetTexture1DLinearMaxWidth(). The number of elements is computed as (sizeInBytes / sizeof(desc)).
 *
 * \par
 * If ::cudaResourceDesc::resType is set to ::cudaResourceTypePitch2D, ::cudaResourceDesc::res::pitch2D::devPtr
 * must be set to a valid device pointer, that is aligned to ::cudaDeviceProp::textureAlignment.
 * ::cudaResourceDesc::res::pitch2D::desc describes the format and the number of components per array element. ::cudaResourceDesc::res::pitch2D::width
 * and ::cudaResourceDesc::res::pitch2D::height specify the width and height of the array in elements, and cannot exceed
 * ::cudaDeviceProp::maxTexture2DLinear[0] and ::cudaDeviceProp::maxTexture2DLinear[1] respectively.
 * ::cudaResourceDesc::res::pitch2D::pitchInBytes specifies the pitch between two rows in bytes and has to be aligned to 
 * ::cudaDeviceProp::texturePitchAlignment. Pitch cannot exceed ::cudaDeviceProp::maxTexture2DLinear[2].
 *
 *
 * The ::cudaTextureDesc struct is defined as
 * \code
        struct cudaTextureDesc {
            enum cudaTextureAddressMode addressMode[3];
            enum cudaTextureFilterMode  filterMode;
            enum cudaTextureReadMode    readMode;
            int                         sRGB;
            float                       borderColor[4];
            int                         normalizedCoords;
            unsigned int                maxAnisotropy;
            enum cudaTextureFilterMode  mipmapFilterMode;
            float                       mipmapLevelBias;
            float                       minMipmapLevelClamp;
            float                       maxMipmapLevelClamp;
            int                         disableTrilinearOptimization;
            int                         seamlessCubemap;
        };
 * \endcode
 * where
 * - ::cudaTextureDesc::addressMode specifies the addressing mode for each dimension of the texture data. ::cudaTextureAddressMode is defined as:
 *   \code
        enum cudaTextureAddressMode {
            cudaAddressModeWrap   = 0,
            cudaAddressModeClamp  = 1,
            cudaAddressModeMirror = 2,
            cudaAddressModeBorder = 3
        };
 *   \endcode
 *   This is ignored if ::cudaResourceDesc::resType is ::cudaResourceTypeLinear. Also, if ::cudaTextureDesc::normalizedCoords
 *   is set to zero, ::cudaAddressModeWrap and ::cudaAddressModeMirror won't be supported and will be switched to ::cudaAddressModeClamp.
 *
 * - ::cudaTextureDesc::filterMode specifies the filtering mode to be used when fetching from the texture. ::cudaTextureFilterMode is defined as:
 *   \code
        enum cudaTextureFilterMode {
            cudaFilterModePoint  = 0,
            cudaFilterModeLinear = 1
        };
 *   \endcode
 *   This is ignored if ::cudaResourceDesc::resType is ::cudaResourceTypeLinear.
 *
 * - ::cudaTextureDesc::readMode specifies whether integer data should be converted to floating point or not. ::cudaTextureReadMode is defined as:
 *   \code
        enum cudaTextureReadMode {
            cudaReadModeElementType     = 0,
            cudaReadModeNormalizedFloat = 1
        };
 *   \endcode
 *   Note that this applies only to 8-bit and 16-bit integer formats. 32-bit integer format would not be promoted, regardless of 
 *   whether or not this ::cudaTextureDesc::readMode is set ::cudaReadModeNormalizedFloat is specified.
 *
 * - ::cudaTextureDesc::sRGB specifies whether sRGB to linear conversion should be performed during texture fetch.
 *
 * - ::cudaTextureDesc::borderColor specifies the float values of color. where:
 *   ::cudaTextureDesc::borderColor[0] contains value of 'R', 
 *   ::cudaTextureDesc::borderColor[1] contains value of 'G',
 *   ::cudaTextureDesc::borderColor[2] contains value of 'B', 
 *   ::cudaTextureDesc::borderColor[3] contains value of 'A'
 *   Note that application using integer border color values will need to <reinterpret_cast> these values to float.
 *   The values are set only when the addressing mode specified by ::cudaTextureDesc::addressMode is cudaAddressModeBorder.
 *
 * - ::cudaTextureDesc::normalizedCoords specifies whether the texture coordinates will be normalized or not.
 *
 * - ::cudaTextureDesc::maxAnisotropy specifies the maximum anistropy ratio to be used when doing anisotropic filtering. This value will be
 *   clamped to the range [1,16].
 *
 * - ::cudaTextureDesc::mipmapFilterMode specifies the filter mode when the calculated mipmap level lies between two defined mipmap levels.
 *
 * - ::cudaTextureDesc::mipmapLevelBias specifies the offset to be applied to the calculated mipmap level.
 *
 * - ::cudaTextureDesc::minMipmapLevelClamp specifies the lower end of the mipmap level range to clamp access to.
 *
 * - ::cudaTextureDesc::maxMipmapLevelClamp specifies the upper end of the mipmap level range to clamp access to.
 *
 * - ::cudaTextureDesc::disableTrilinearOptimization specifies whether the trilinear filtering optimizations will be disabled.
 *
 * - ::cudaTextureDesc::seamlessCubemap specifies whether seamless cube map filtering is enabled. This flag can only be specified if the 
 *   underlying resource is a CUDA array or a CUDA mipmapped array that was created with the flag ::cudaArrayCubemap.
 *   When seamless cube map filtering is enabled, texture address modes specified by ::cudaTextureDesc::addressMode are ignored.
 *   Instead, if the ::cudaTextureDesc::filterMode is set to ::cudaFilterModePoint the address mode ::cudaAddressModeClamp will be applied for all dimensions.
 *   If the ::cudaTextureDesc::filterMode is set to ::cudaFilterModeLinear seamless cube map filtering will be performed when sampling along the cube face borders.
 *
 * The ::cudaResourceViewDesc struct is defined as
 * \code
        struct cudaResourceViewDesc {
            enum cudaResourceViewFormat format;
            size_t                      width;
            size_t                      height;
            size_t                      depth;
            unsigned int                firstMipmapLevel;
            unsigned int                lastMipmapLevel;
            unsigned int                firstLayer;
            unsigned int                lastLayer;
        };
 * \endcode
 * where:
 * - ::cudaResourceViewDesc::format specifies how the data contained in the CUDA array or CUDA mipmapped array should
 *   be interpreted. Note that this can incur a change in size of the texture data. If the resource view format is a block
 *   compressed format, then the underlying CUDA array or CUDA mipmapped array has to have a 32-bit unsigned integer format
 *   with 2 or 4 channels, depending on the block compressed format. For ex., BC1 and BC4 require the underlying CUDA array to have
 *   a 32-bit unsigned int with 2 channels. The other BC formats require the underlying resource to have the same 32-bit unsigned int
 *   format but with 4 channels.
 *
 * - ::cudaResourceViewDesc::width specifies the new width of the texture data. If the resource view format is a block
 *   compressed format, this value has to be 4 times the original width of the resource. For non block compressed formats,
 *   this value has to be equal to that of the original resource.
 *
 * - ::cudaResourceViewDesc::height specifies the new height of the texture data. If the resource view format is a block
 *   compressed format, this value has to be 4 times the original height of the resource. For non block compressed formats,
 *   this value has to be equal to that of the original resource.
 *
 * - ::cudaResourceViewDesc::depth specifies the new depth of the texture data. This value has to be equal to that of the
 *   original resource.
 *
 * - ::cudaResourceViewDesc::firstMipmapLevel specifies the most detailed mipmap level. This will be the new mipmap level zero.
 *   For non-mipmapped resources, this value has to be zero.::cudaTextureDesc::minMipmapLevelClamp and ::cudaTextureDesc::maxMipmapLevelClamp
 *   will be relative to this value. For ex., if the firstMipmapLevel is set to 2, and a minMipmapLevelClamp of 1.2 is specified,
 *   then the actual minimum mipmap level clamp will be 3.2.
 *
 * - ::cudaResourceViewDesc::lastMipmapLevel specifies the least detailed mipmap level. For non-mipmapped resources, this value
 *   has to be zero.
 *
 * - ::cudaResourceViewDesc::firstLayer specifies the first layer index for layered textures. This will be the new layer zero.
 *   For non-layered resources, this value has to be zero.
 *
 * - ::cudaResourceViewDesc::lastLayer specifies the last layer index for layered textures. For non-layered resources, 
 *   this value has to be zero.
 *
 *
 * \param pTexObject   - Texture object to create
 * \param pResDesc     - Resource descriptor
 * \param pTexDesc     - Texture descriptor
 * \param pResViewDesc - Resource view descriptor
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDestroyTextureObject,
 * ::cuTexObjectCreate
 */

extern __host__ cudaError_t CUDARTAPI cudaCreateTextureObject(cudaTextureObject_t *pTexObject, const struct cudaResourceDesc *pResDesc, const struct cudaTextureDesc *pTexDesc, const struct cudaResourceViewDesc *pResViewDesc);

/**
 * \brief Destroys a texture object
 *
 * Destroys the texture object specified by \p texObject.
 *
 * \param texObject - Texture object to destroy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa
 * ::cudaCreateTextureObject,
 * ::cuTexObjectDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaDestroyTextureObject(cudaTextureObject_t texObject);

/**
 * \brief Returns a texture object's resource descriptor
 *
 * Returns the resource descriptor for the texture object specified by \p texObject.
 *
 * \param pResDesc  - Resource descriptor
 * \param texObject - Texture object
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaCreateTextureObject,
 * ::cuTexObjectGetResourceDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaGetTextureObjectResourceDesc(struct cudaResourceDesc *pResDesc, cudaTextureObject_t texObject);

/**
 * \brief Returns a texture object's texture descriptor
 *
 * Returns the texture descriptor for the texture object specified by \p texObject.
 *
 * \param pTexDesc  - Texture descriptor
 * \param texObject - Texture object
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaCreateTextureObject,
 * ::cuTexObjectGetTextureDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaGetTextureObjectTextureDesc(struct cudaTextureDesc *pTexDesc, cudaTextureObject_t texObject);

/**
 * \brief Returns a texture object's resource view descriptor
 *
 * Returns the resource view descriptor for the texture object specified by \p texObject.
 * If no resource view was specified, ::cudaErrorInvalidValue is returned.
 *
 * \param pResViewDesc - Resource view descriptor
 * \param texObject    - Texture object
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaCreateTextureObject,
 * ::cuTexObjectGetResourceViewDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaGetTextureObjectResourceViewDesc(struct cudaResourceViewDesc *pResViewDesc, cudaTextureObject_t texObject);

/** @} */ /* END CUDART_TEXTURE_OBJECT */

/**
 * \defgroup CUDART_SURFACE_OBJECT Surface Object Management
 *
 * ___MANBRIEF___ surface object management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the low level texture object management functions
 * of the CUDA runtime application programming interface. The surface object 
 * API is only supported on devices of compute capability 3.0 or higher.
 *
 * @{
 */

/**
 * \brief Creates a surface object
 *
 * Creates a surface object and returns it in \p pSurfObject. \p pResDesc describes
 * the data to perform surface load/stores on. ::cudaResourceDesc::resType must be 
 * ::cudaResourceTypeArray and  ::cudaResourceDesc::res::array::array
 * must be set to a valid CUDA array handle.
 *
 * Surface objects are only supported on devices of compute capability 3.0 or higher.
 * Additionally, a surface object is an opaque value, and, as such, should only be
 * accessed through CUDA API calls.
 *
 * \param pSurfObject - Surface object to create
 * \param pResDesc    - Resource descriptor
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidChannelDescriptor,
 * ::cudaErrorInvalidResourceHandle
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDestroySurfaceObject,
 * ::cuSurfObjectCreate
 */

extern __host__ cudaError_t CUDARTAPI cudaCreateSurfaceObject(cudaSurfaceObject_t *pSurfObject, const struct cudaResourceDesc *pResDesc);

/**
 * \brief Destroys a surface object
 *
 * Destroys the surface object specified by \p surfObject.
 *
 * \param surfObject - Surface object to destroy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa
 * ::cudaCreateSurfaceObject,
 * ::cuSurfObjectDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaDestroySurfaceObject(cudaSurfaceObject_t surfObject);

/**
 * \brief Returns a surface object's resource descriptor
 * Returns the resource descriptor for the surface object specified by \p surfObject.
 *
 * \param pResDesc   - Resource descriptor
 * \param surfObject - Surface object
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaCreateSurfaceObject,
 * ::cuSurfObjectGetResourceDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaGetSurfaceObjectResourceDesc(struct cudaResourceDesc *pResDesc, cudaSurfaceObject_t surfObject);

/** @} */ /* END CUDART_SURFACE_OBJECT */

/**
 * \defgroup CUDART__VERSION Version Management
 *
 * @{
 */

/**
 * \brief Returns the latest version of CUDA supported by the driver
 *
 * Returns in \p *driverVersion the latest version of CUDA supported by
 * the driver. The version is returned as (1000 &times; major + 10 &times; minor).
 * For example, CUDA 9.2 would be represented by 9020. If no driver is installed,
 * then 0 is returned as the driver version.
 *
 * This function automatically returns ::cudaErrorInvalidValue
 * if \p driverVersion is NULL.
 *
 * \param driverVersion - Returns the CUDA driver version.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaRuntimeGetVersion,
 * ::cuDriverGetVersion
 */
extern __host__ cudaError_t CUDARTAPI cudaDriverGetVersion(int *driverVersion);

/**
 * \brief Returns the CUDA Runtime version
 *
 * Returns in \p *runtimeVersion the version number of the current CUDA
 * Runtime instance. The version is returned as
 * (1000 &times; major + 10 &times; minor). For example,
 * CUDA 9.2 would be represented by 9020.
 *
 * As of CUDA 12.0, this function no longer initializes CUDA. The purpose
 * of this API is solely to return a compile-time constant stating the
 * CUDA Toolkit version in the above format.
 *
 * This function automatically returns ::cudaErrorInvalidValue if
 * the \p runtimeVersion argument is NULL.
 *
 * \param runtimeVersion - Returns the CUDA Runtime version.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDriverGetVersion,
 * ::cuDriverGetVersion
 */
extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaRuntimeGetVersion(int *runtimeVersion);

/** @} */ /* END CUDART__VERSION */

/**
 * \defgroup CUDART_LOGS Error Log Management Functions
 *
 * ___MANBRIEF___ error log management interface for the CUDA Runtime and Driver
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the error log management functions of the CUDA runtime
 * application programming interface. The Error Log Management interface will operate
 * on both the CUDA Driver and CUDA Runtime.
 *
 * @{
 */

/**
 * Type of public error reporting callback functions.
 * \param data User parameter provided at registration
 * \param logLevel Severity level of the log message
 * \param message Error log message being reported
 * \param length Length of the message in bytes
 */
typedef void (CUDART_CB *cudaLogsCallback_t)(void *data, cudaLogLevel logLevel, char *message, size_t length);

/**
 * \brief Register a callback function to receive error log messages
 * 
 * \param callbackFunc  - The function to register as a callback
 * \param userData      - A generic pointer to user data. This is passed into the callback function.
 * \param callback_out  - Optional location to store the callback handle after it is registered
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 */
extern __host__ cudaError_t CUDARTAPI cudaLogsRegisterCallback(cudaLogsCallback_t callbackFunc, void *userData, cudaLogsCallbackHandle *callback_out);

/**
 * \brief Unregister a log message callback
 * 
 * \param callback  - The callback instance to unregister from receiving log messages
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 */
extern __host__ cudaError_t CUDARTAPI cudaLogsUnregisterCallback(cudaLogsCallbackHandle callback);

/**
 * \brief Sets log iterator to point to the end of log buffer, where the next message would be written.
 * 
 * \param iterator_out - Location to store an iterator to the current tail of the logs
 * \param flags        - Reserved for future use, must be 0
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 */
extern __host__ cudaError_t CUDARTAPI cudaLogsCurrent(cudaLogIterator *iterator_out, unsigned int flags);

/**
 * \brief Dump accumulated driver logs into a file
 *
 * Logs generated by the driver are stored in an internal buffer and can be copied out using this API.
 * This API dumps all driver logs starting from \p iterator into \p pathToFile provided.
 *
 * \note \p iterator is auto-advancing. Dumping logs will update the value of
 *       \p iterator to receive the next generated log.
 *
 * \note The driver reserves limited memory for storing logs.
 *       The oldest logs may be overwritten and become unrecoverable. An indication will appear in the
 *       destination outupt if the logs have been truncated. Call dump after each failed API to mitigate this 
 *       risk.
 *
 * \param iterator   - Optional auto-advancing iterator specifying the starting log to read. NULL value dumps all logs.
 * \param pathToFile - Path to output file for dumping logs
 * \param flags      - Reserved for future use, must be 0
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 */
extern __host__ cudaError_t CUDARTAPI cudaLogsDumpToFile(cudaLogIterator *iterator, const char *pathToFile, unsigned int flags);

/**
 * \brief Dump accumulated driver logs into a buffer
 *
 * Logs generated by the driver are stored in an internal buffer and can be copied out using this API.
 * This API dumps driver logs from \p iterator into \p buffer up to the size specified in \p *size.
 * The driver will always null terminate the buffer but there will not be a null character between log 
 * entries, only a newline \\n. The driver will then return the actual number of bytes written in 
 * \p *size, excluding the null terminator. If there are no messages to dump, \p *size will be set to 0
 * and the function will return ::CUDA_SUCCESS. 
 * If the provided \p buffer is not large enough to hold any messages, \p *size will be set to 0 and
 * the function will return ::CUDA_ERROR_INVALID_VALUE.
 *
 * \note \p iterator is auto-advancing. Dumping logs will update the value of
 *       \p iterator to receive the next generated log.
 *
 * \note The driver reserves limited memory for storing logs. The maximum size of the buffer is 25600 bytes.
 *       The oldest logs may be overwritten and become unrecoverable. An indication will appear in the
 *       destination outupt if the logs have been truncated. Call dump after each failed API to mitigate this 
 *       risk.
 *
 * \note If the provided value in \p *size is not large enough to hold all buffered messages, a message will
 *       be added at the head of the buffer indicating this. The driver then computes the number of messages
 *       it is able to store in \p buffer and writes it out. The final message in \p buffer will always be
 *       the most recent log message as of when the API is called.
 *
 * \param iterator  - Optional auto-advancing iterator specifying the starting log to read. NULL value dumps all logs.
 * \param buffer    - Pointer to dump logs
 * \param size      - See description
 * \param flags     - Reserved for future use, must be 0
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 */
extern __host__ cudaError_t CUDARTAPI cudaLogsDumpToMemory(cudaLogIterator *iterator, char *buffer, size_t *size, unsigned int flags);

 /** @} */ /* END CUDART_LOGS */

/**
 * \defgroup CUDART_GRAPH Graph Management
 *
 * ___MANBRIEF___ graph management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the graph management functions of CUDA
 * runtime application programming interface.
 *
 * @{
 */

/**
 * \brief Creates a graph
 *
 * Creates an empty graph, which is returned via \p pGraph.
 *
 * \param pGraph - Returns newly created graph
 * \param flags   - Graph creation flags, must be 0
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode,
 * ::cudaGraphInstantiate,
 * ::cudaGraphDestroy,
 * ::cudaGraphGetNodes,
 * ::cudaGraphGetRootNodes,
 * ::cudaGraphGetEdges,
 * ::cudaGraphClone
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphCreate(cudaGraph_t *pGraph, unsigned int flags __dv(0));

/**
 * \brief Creates a kernel execution node and adds it to a graph
 *
 * Creates a new kernel execution node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies and arguments specified in \p pNodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * The cudaKernelNodeParams structure is defined as:
 *
 * \code
 *  struct cudaKernelNodeParams
 *  {
 *      void* func;
 *      dim3 gridDim;
 *      dim3 blockDim;
 *      unsigned int sharedMemBytes;
 *      void **kernelParams;
 *      void **extra;
 *  };
 * \endcode
 *
 * When the graph is launched, the node will invoke kernel \p func on a (\p gridDim.x x
 * \p gridDim.y x \p gridDim.z) grid of blocks. Each block contains
 * (\p blockDim.x x \p blockDim.y x \p blockDim.z) threads.
 *
 * \p sharedMem sets the amount of dynamic shared memory that will be
 * available to each thread block.
 *
 * Kernel parameters to \p func can be specified in one of two ways:
 *
 * 1) Kernel parameters can be specified via \p kernelParams. If the kernel has N
 * parameters, then \p kernelParams needs to be an array of N pointers. Each pointer,
 * from \p kernelParams[0] to \p kernelParams[N-1], points to the region of memory from which the actual
 * parameter will be copied. The number of kernel parameters and their offsets and sizes do not need
 * to be specified as that information is retrieved directly from the kernel's image.
 *
 * 2) Kernel parameters can also be packaged by the application into a single buffer that is passed in
 * via \p extra. This places the burden on the application of knowing each kernel
 * parameter's size and alignment/padding within the buffer. The \p extra parameter exists
 * to allow this function to take additional less commonly used arguments. \p extra specifies
 * a list of names of extra settings and their corresponding values. Each extra setting name is
 * immediately followed by the corresponding value. The list must be terminated with either NULL or
 * CU_LAUNCH_PARAM_END.
 *
 * - ::CU_LAUNCH_PARAM_END, which indicates the end of the \p extra
 *   array;
 * - ::CU_LAUNCH_PARAM_BUFFER_POINTER, which specifies that the next
 *   value in \p extra will be a pointer to a buffer
 *   containing all the kernel parameters for launching kernel
 *   \p func;
 * - ::CU_LAUNCH_PARAM_BUFFER_SIZE, which specifies that the next
 *   value in \p extra will be a pointer to a size_t
 *   containing the size of the buffer specified with
 *   ::CU_LAUNCH_PARAM_BUFFER_POINTER;
 *
 * The error ::cudaErrorInvalidValue will be returned if kernel parameters are specified with both
 * \p kernelParams and \p extra (i.e. both \p kernelParams and
 * \p extra are non-NULL).
 *
 * The \p kernelParams or \p extra array, as well as the argument values it points to,
 * are copied during this call.
 *
 * \note Kernels launched using graphs must not use texture and surface references. Reading or
 *       writing through any texture or surface reference is undefined behavior.
 *       This restriction does not apply to texture and surface objects.
 *
 * \param pGraphNode     - Returns newly created node
 * \param graph          - Graph to which to add the node
 * \param pDependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param pNodeParams      - Parameters for the GPU execution node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDeviceFunction
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaLaunchKernel,
 * ::cudaGraphKernelNodeGetParams,
 * ::cudaGraphKernelNodeSetParams,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddKernelNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaKernelNodeParams *pNodeParams);

/**
 * \brief Returns a kernel node's parameters
 *
 * Returns the parameters of kernel node \p node in \p pNodeParams.
 * The \p kernelParams or \p extra array returned in \p pNodeParams,
 * as well as the argument values it points to, are owned by the node.
 * This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cudaGraphKernelNodeSetParams to update the
 * parameters of this node.
 *
 * The params will contain either \p kernelParams or \p extra,
 * according to which of these was most recently set on the node.
 *
 * \param node        - Node to get the parameters for
 * \param pNodeParams - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDeviceFunction
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaLaunchKernel,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphKernelNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeGetParams(cudaGraphNode_t node, struct cudaKernelNodeParams *pNodeParams);

/**
 * \brief Sets a kernel node's parameters
 *
 * Sets the parameters of kernel node \p node to \p pNodeParams.
 *
 * \param node        - Node to set the parameters for
 * \param pNodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorMemoryAllocation
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaLaunchKernel,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphKernelNodeGetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeSetParams(cudaGraphNode_t node, const struct cudaKernelNodeParams *pNodeParams);

/**
 * \brief Copies attributes from source node to destination node.
 *
 * Copies attributes from source node \p hSrc to destination node \p hDst.
 * Both node must have the same context.
 *
 * \param[out] hDst Destination node
 * \param[in] hSrc Source node
 * For list of attributes see ::cudaKernelNodeAttrID
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidContext
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeCopyAttributes(
        cudaGraphNode_t hDst,
        cudaGraphNode_t hSrc);

/**
 * \brief Queries node attribute.
 *
 * Queries attribute \p attr from node \p hNode and stores it in corresponding
 * member of \p value_out.
 *
 * \param[in] hNode
 * \param[in] attr
 * \param[out] value_out
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeGetAttribute(
    cudaGraphNode_t hNode,
    cudaKernelNodeAttrID attr,
    cudaKernelNodeAttrValue *value_out);

/**
 * \brief Sets node attribute.
 *
 * Sets attribute \p attr on node \p hNode from corresponding attribute of
 * \p value.
 *
 * \param[out] hNode
 * \param[in] attr
 * \param[out] value
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 * \notefnerr
 *
 * \sa
 * ::cudaAccessPolicyWindow
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeSetAttribute(
    cudaGraphNode_t hNode,
    cudaKernelNodeAttrID attr,
    const cudaKernelNodeAttrValue *value);

/**
 * \brief Creates a memcpy node and adds it to a graph
 *
 * Creates a new memcpy node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * When the graph is launched, the node will perform the memcpy described by \p pCopyParams.
 * See ::cudaMemcpy3D() for a description of the structure and its restrictions.
 *
 * Memcpy nodes have some additional restrictions with regards to managed memory, if the
 * system contains at least one device which has a zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess.
 *
 * \param pGraphNode     - Returns newly created node
 * \param graph          - Graph to which to add the node
 * \param pDependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param pCopyParams      - Parameters for the memory copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaMemcpy3D,
 * ::cudaGraphAddMemcpyNodeToSymbol,
 * ::cudaGraphAddMemcpyNodeFromSymbol,
 * ::cudaGraphAddMemcpyNode1D,
 * ::cudaGraphMemcpyNodeGetParams,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemsetNode
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaMemcpy3DParms *pCopyParams);

/**
 * \brief Creates a memcpy node to copy to a symbol on the device and adds it to a graph
 *
 * Creates a new memcpy node to copy to \p symbol and adds it to \p graph with
 * \p numDependencies dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * When the graph is launched, the node will copy \p count bytes from the memory area
 * pointed to by \p src to the memory area pointed to by \p offset bytes from the start
 * of symbol \p symbol. The memory areas may not overlap. \p symbol is a variable that
 * resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of
 * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault
 * is only allowed on systems that support unified virtual addressing.
 *
 * Memcpy nodes have some additional restrictions with regards to managed memory, if the
 * system contains at least one device which has a zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param symbol          - Device symbol address
 * \param src             - Source memory address
 * \param count           - Size in bytes to copy
 * \param offset          - Offset from start of symbol in bytes
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMemcpyToSymbol,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemcpyNodeFromSymbol,
 * ::cudaGraphMemcpyNodeGetParams,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNodeToSymbol(
    cudaGraphNode_t *pGraphNode,
    cudaGraph_t graph,
    const cudaGraphNode_t *pDependencies,
    size_t numDependencies,
    const void* symbol,
    const void* src,
    size_t count,
    size_t offset,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Creates a memcpy node to copy from a symbol on the device and adds it to a graph
 *
 * Creates a new memcpy node to copy from \p symbol and adds it to \p graph with
 * \p numDependencies dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * When the graph is launched, the node will copy \p count bytes from the memory area
 * pointed to by \p offset bytes from the start of symbol \p symbol to the memory area
 *  pointed to by \p dst. The memory areas may not overlap. \p symbol is a variable
 *  that resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer
 * is inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * Memcpy nodes have some additional restrictions with regards to managed memory, if the
 * system contains at least one device which has a zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param dst             - Destination memory address
 * \param symbol          - Device symbol address
 * \param count           - Size in bytes to copy
 * \param offset          - Offset from start of symbol in bytes
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMemcpyFromSymbol,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemcpyNodeToSymbol,
 * ::cudaGraphMemcpyNodeGetParams,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNodeFromSymbol(
    cudaGraphNode_t* pGraphNode,
    cudaGraph_t graph,
    const cudaGraphNode_t* pDependencies,
    size_t numDependencies,
    void* dst,
    const void* symbol,
    size_t count,
    size_t offset,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Creates a 1D memcpy node and adds it to a graph
 *
 * Creates a new 1D memcpy node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * When the graph is launched, the node will copy \p count bytes from the memory
 * area pointed to by \p src to the memory area pointed to by \p dst, where
 * \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing. Launching a
 * memcpy node with dst and src pointers that do not match the direction of
 * the copy results in an undefined behavior.
 *
 * Memcpy nodes have some additional restrictions with regards to managed memory, if the
 * system contains at least one device which has a zero value for the device attribute
 * ::cudaDevAttrConcurrentManagedAccess.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param dst             - Destination memory address
 * \param src             - Source memory address
 * \param count           - Size in bytes to copy
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMemcpy,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeGetParams,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParams1D,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNode1D(
    cudaGraphNode_t *pGraphNode,
    cudaGraph_t graph,
    const cudaGraphNode_t *pDependencies,
    size_t numDependencies,
    void* dst,
    const void* src,
    size_t count,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Returns a memcpy node's parameters
 *
 * Returns the parameters of memcpy node \p node in \p pNodeParams.
 *
 * \param node        - Node to get the parameters for
 * \param pNodeParams - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaMemcpy3D,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeGetParams(cudaGraphNode_t node, struct cudaMemcpy3DParms *pNodeParams);

/**
 * \brief Sets a memcpy node's parameters
 *
 * Sets the parameters of memcpy node \p node to \p pNodeParams.
 *
 * \param node        - Node to set the parameters for
 * \param pNodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaMemcpy3D,
 * ::cudaGraphMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphMemcpyNodeSetParams1D,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeGetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParams(cudaGraphNode_t node, const struct cudaMemcpy3DParms *pNodeParams);

/**
 * \brief Sets a memcpy node's parameters to copy to a symbol on the device
 *
 * Sets the parameters of memcpy node \p node to the copy described by the provided parameters.
 *
 * When the graph is launched, the node will copy \p count bytes from the memory area
 * pointed to by \p src to the memory area pointed to by \p offset bytes from the start
 * of symbol \p symbol. The memory areas may not overlap. \p symbol is a variable that
 * resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of
 * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault
 * is only allowed on systems that support unified virtual addressing.
 *
 * \param node            - Node to set the parameters for
 * \param symbol          - Device symbol address
 * \param src             - Source memory address
 * \param count           - Size in bytes to copy
 * \param offset          - Offset from start of symbol in bytes
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMemcpyToSymbol,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeGetParams
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParamsToSymbol(
    cudaGraphNode_t node,
    const void* symbol,
    const void* src,
    size_t count,
    size_t offset,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Sets a memcpy node's parameters to copy from a symbol on the device
 *
 * Sets the parameters of memcpy node \p node to the copy described by the provided parameters.
 *
 * When the graph is launched, the node will copy \p count bytes from the memory area
 * pointed to by \p offset bytes from the start of symbol \p symbol to the memory area
 *  pointed to by \p dst. The memory areas may not overlap. \p symbol is a variable
 *  that resides in global or constant memory space. \p kind can be either
 * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault.
 * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer
 * is inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing.
 *
 * \param node            - Node to set the parameters for
 * \param dst             - Destination memory address
 * \param symbol          - Device symbol address
 * \param count           - Size in bytes to copy
 * \param offset          - Offset from start of symbol in bytes
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMemcpyFromSymbol,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeGetParams
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParamsFromSymbol(
    cudaGraphNode_t node,
    void* dst,
    const void* symbol,
    size_t count,
    size_t offset,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Sets a memcpy node's parameters to perform a 1-dimensional copy
 *
 * Sets the parameters of memcpy node \p node to the copy described by the provided parameters.
 *
 * When the graph is launched, the node will copy \p count bytes from the memory
 * area pointed to by \p src to the memory area pointed to by \p dst, where
 * \p kind specifies the direction of the copy, and must be one of
 * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost,
 * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing
 * ::cudaMemcpyDefault is recommended, in which case the type of transfer is
 * inferred from the pointer values. However, ::cudaMemcpyDefault is only
 * allowed on systems that support unified virtual addressing. Launching a
 * memcpy node with dst and src pointers that do not match the direction of
 * the copy results in an undefined behavior.
 *
 * \param node            - Node to set the parameters for
 * \param dst             - Destination memory address
 * \param src             - Source memory address
 * \param count           - Size in bytes to copy
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaMemcpy,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeGetParams
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParams1D(
    cudaGraphNode_t node,
    void* dst,
    const void* src,
    size_t count,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Creates a memset node and adds it to a graph
 *
 * Creates a new memset node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * The element size must be 1, 2, or 4 bytes.
 * When the graph is launched, the node will perform the memset described by \p pMemsetParams.
 *
 * \param pGraphNode     - Returns newly created node
 * \param graph          - Graph to which to add the node
 * \param pDependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param pMemsetParams    - Parameters for the memory set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaMemset2D,
 * ::cudaGraphMemsetNodeGetParams,
 * ::cudaGraphMemsetNodeSetParams,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemcpyNode
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemsetNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaMemsetParams *pMemsetParams);

/**
 * \brief Returns a memset node's parameters
 *
 * Returns the parameters of memset node \p node in \p pNodeParams.
 *
 * \param node        - Node to get the parameters for
 * \param pNodeParams - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaMemset2D,
 * ::cudaGraphAddMemsetNode,
 * ::cudaGraphMemsetNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphMemsetNodeGetParams(cudaGraphNode_t node, struct cudaMemsetParams *pNodeParams);

/**
 * \brief Sets a memset node's parameters
 *
 * Sets the parameters of memset node \p node to \p pNodeParams.
 *
 * \param node        - Node to set the parameters for
 * \param pNodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaMemset2D,
 * ::cudaGraphAddMemsetNode,
 * ::cudaGraphMemsetNodeGetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphMemsetNodeSetParams(cudaGraphNode_t node, const struct cudaMemsetParams *pNodeParams);

/**
 * \brief Creates a host execution node and adds it to a graph
 *
 * Creates a new CPU execution node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies and arguments specified in \p pNodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * When the graph is launched, the node will invoke the specified CPU function.
 * Host nodes are not supported under MPS with pre-Volta GPUs.
 *
 * \param pGraphNode     - Returns newly created node
 * \param graph          - Graph to which to add the node
 * \param pDependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param pNodeParams      - Parameters for the host node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaLaunchHostFunc,
 * ::cudaGraphHostNodeGetParams,
 * ::cudaGraphHostNodeSetParams,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddHostNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaHostNodeParams *pNodeParams);

/**
 * \brief Returns a host node's parameters
 *
 * Returns the parameters of host node \p node in \p pNodeParams.
 *
 * \param node        - Node to get the parameters for
 * \param pNodeParams - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaLaunchHostFunc,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphHostNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphHostNodeGetParams(cudaGraphNode_t node, struct cudaHostNodeParams *pNodeParams);

/**
 * \brief Sets a host node's parameters
 *
 * Sets the parameters of host node \p node to \p nodeParams.
 *
 * \param node        - Node to set the parameters for
 * \param pNodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaLaunchHostFunc,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphHostNodeGetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphHostNodeSetParams(cudaGraphNode_t node, const struct cudaHostNodeParams *pNodeParams);

/**
 * \brief Creates a child graph node and adds it to a graph
 *
 * Creates a new node which executes an embedded graph, and adds it to \p graph with
 * \p numDependencies dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * If \p childGraph contains allocation nodes, free nodes, or conditional nodes, this call will
 * return an error.
 *
 * The node executes an embedded child graph. The child graph is cloned in this call.
 *
 * \param pGraphNode     - Returns newly created node
 * \param graph          - Graph to which to add the node
 * \param pDependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param childGraph      - The graph to clone into this node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphChildGraphNodeGetGraph,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode,
 * ::cudaGraphClone
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddChildGraphNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, cudaGraph_t childGraph);

/**
 * \brief Gets a handle to the embedded graph of a child graph node
 *
 * Gets a handle to the embedded graph in a child graph node. This call
 * does not clone the graph. Changes to the graph will be reflected in
 * the node, and the node retains ownership of the graph.
 *
 * Allocation and free nodes cannot be added to the returned graph.
 * Attempting to do so will return an error.
 *
 * \param node   - Node to get the embedded graph for
 * \param pGraph - Location to store a handle to the graph
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphNodeFindInClone
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphChildGraphNodeGetGraph(cudaGraphNode_t node, cudaGraph_t *pGraph);

/**
 * \brief Creates an empty node and adds it to a graph
 *
 * Creates a new node which performs no operation, and adds it to \p graph with
 * \p numDependencies dependencies specified via \p pDependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p pGraphNode.
 *
 * An empty node performs no operation during execution, but can be used for
 * transitive ordering. For example, a phased execution graph with 2 groups of n
 * nodes with a barrier between them can be represented using an empty node and
 * 2*n dependency edges, rather than no empty node and n^2 dependency edges.
 *
 * \param pGraphNode     - Returns newly created node
 * \param graph          - Graph to which to add the node
 * \param pDependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddEmptyNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies);

/**
 * \brief Creates an event record node and adds it to a graph
 *
 * Creates a new event record node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and event specified in \p event.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * Each launch of the graph will record \p event to capture execution of the
 * node's dependencies.
 *
 * These nodes may not be used in loops or conditionals.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param event           - Event for the node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphAddEventRecordNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, cudaEvent_t event);
#endif

/**
 * \brief Returns the event associated with an event record node
 *
 * Returns the event of event record node \p hNode in \p event_out.
 *
 * \param hNode     - Node to get the event for
 * \param event_out - Pointer to return the event
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphEventRecordNodeSetEvent,
 * ::cudaGraphEventWaitNodeGetEvent,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphEventRecordNodeGetEvent(cudaGraphNode_t node, cudaEvent_t *event_out);
#endif

/**
 * \brief Sets an event record node's event
 *
 * Sets the event of event record node \p hNode to \p event.
 *
 * \param hNode - Node to set the event for
 * \param event - Event to use
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphEventRecordNodeGetEvent,
 * ::cudaGraphEventWaitNodeSetEvent,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphEventRecordNodeSetEvent(cudaGraphNode_t node, cudaEvent_t event);
#endif

/**
 * \brief Creates an event wait node and adds it to a graph
 *
 * Creates a new event wait node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and event specified in \p event.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * The graph node will wait for all work captured in \p event.  See ::cuEventRecord()
 * for details on what is captured by an event.  The synchronization will be performed
 * efficiently on the device when applicable.  \p event may be from a different context
 * or device than the launch stream.
 *
 * These nodes may not be used in loops or conditionals.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param event           - Event for the node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphAddEventWaitNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, cudaEvent_t event);
#endif

/**
 * \brief Returns the event associated with an event wait node
 *
 * Returns the event of event wait node \p hNode in \p event_out.
 *
 * \param hNode     - Node to get the event for
 * \param event_out - Pointer to return the event
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphEventWaitNodeSetEvent,
 * ::cudaGraphEventRecordNodeGetEvent,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphEventWaitNodeGetEvent(cudaGraphNode_t node, cudaEvent_t *event_out);
#endif

/**
 * \brief Sets an event wait node's event
 *
 * Sets the event of event wait node \p hNode to \p event.
 *
 * \param hNode - Node to set the event for
 * \param event - Event to use
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphEventWaitNodeGetEvent,
 * ::cudaGraphEventRecordNodeSetEvent,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphEventWaitNodeSetEvent(cudaGraphNode_t node, cudaEvent_t event);
#endif

/**
 * \brief Creates an external semaphore signal node and adds it to a graph
 *
 * Creates a new external semaphore signal node and adds it to \p graph with \p
 * numDependencies dependencies specified via \p dependencies and arguments specified
 * in \p nodeParams. It is possible for \p numDependencies to be 0, in which case the
 * node will be placed at the root of the graph. \p dependencies may not have any
 * duplicate entries. A handle to the new node will be returned in \p pGraphNode.
 *
 * Performs a signal operation on a set of externally allocated semaphore objects
 * when the node is launched.  The operation(s) will occur after all of the node's
 * dependencies have completed.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphExternalSemaphoresSignalNodeGetParams,
 * ::cudaGraphExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaImportExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphAddExternalSemaphoresSignalNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaExternalSemaphoreSignalNodeParams *nodeParams);
#endif

/**
 * \brief Returns an external semaphore signal node's parameters
 *
 * Returns the parameters of an external semaphore signal node \p hNode in \p params_out.
 * The \p extSemArray and \p paramsArray returned in \p params_out,
 * are owned by the node.  This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cudaGraphExternalSemaphoresSignalNodeSetParams to update the
 * parameters of this node.
 *
 * \param hNode      - Node to get the parameters for
 * \param params_out - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaLaunchKernel,
 * ::cudaGraphAddExternalSemaphoresSignalNode,
 * ::cudaGraphExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresSignalNodeGetParams(cudaGraphNode_t hNode, struct cudaExternalSemaphoreSignalNodeParams *params_out);
#endif

/**
 * \brief Sets an external semaphore signal node's parameters
 *
 * Sets the parameters of an external semaphore signal node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresSignalNode,
 * ::cudaGraphExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresSignalNodeSetParams(cudaGraphNode_t hNode, const struct cudaExternalSemaphoreSignalNodeParams *nodeParams);
#endif

/**
 * \brief Creates an external semaphore wait node and adds it to a graph
 *
 * Creates a new external semaphore wait node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries. A handle
 * to the new node will be returned in \p pGraphNode.
 *
 * Performs a wait operation on a set of externally allocated semaphore objects
 * when the node is launched.  The node's dependencies will not be launched until
 * the wait operation has completed.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphExternalSemaphoresWaitNodeGetParams,
 * ::cudaGraphExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresSignalNode,
 * ::cudaImportExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphAddExternalSemaphoresWaitNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaExternalSemaphoreWaitNodeParams *nodeParams);
#endif

/**
 * \brief Returns an external semaphore wait node's parameters
 *
 * Returns the parameters of an external semaphore wait node \p hNode in \p params_out.
 * The \p extSemArray and \p paramsArray returned in \p params_out,
 * are owned by the node.  This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cudaGraphExternalSemaphoresSignalNodeSetParams to update the
 * parameters of this node.
 *
 * \param hNode      - Node to get the parameters for
 * \param params_out - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaLaunchKernel,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaGraphExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresWaitNodeGetParams(cudaGraphNode_t hNode, struct cudaExternalSemaphoreWaitNodeParams *params_out);
#endif

/**
 * \brief Sets an external semaphore wait node's parameters
 *
 * Sets the parameters of an external semaphore wait node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaGraphExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresWaitNodeSetParams(cudaGraphNode_t hNode, const struct cudaExternalSemaphoreWaitNodeParams *nodeParams);
#endif

/**
 * \brief Creates an allocation node and adds it to a graph
 *
 * Creates a new allocation node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries. A handle
 * to the new node will be returned in \p pGraphNode.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * When ::cudaGraphAddMemAllocNode creates an allocation node, it returns the address of the allocation in
 * \p nodeParams.dptr.  The allocation's address remains fixed across instantiations and launches.
 *
 * If the allocation is freed in the same graph, by creating a free node using ::cudaGraphAddMemFreeNode,
 * the allocation can be accessed by nodes ordered after the allocation node but before the free node.
 * These allocations cannot be freed outside the owning graph, and they can only be freed once in the
 * owning graph.
 *
 * If the allocation is not freed in the same graph, then it can be accessed not only by nodes in the
 * graph which are ordered after the allocation node, but also by stream operations ordered after the
 * graph's execution but before the allocation is freed.
 *
 * Allocations which are not freed in the same graph can be freed by:
 * - passing the allocation to ::cudaMemFreeAsync or ::cudaMemFree;
 * - launching a graph with a free node for that allocation; or
 * - specifying ::cudaGraphInstantiateFlagAutoFreeOnLaunch during instantiation, which makes
 *   each launch behave as though it called ::cudaMemFreeAsync for every unfreed allocation.
 *
 * It is not possible to free an allocation in both the owning graph and another graph.  If the allocation
 * is freed in the same graph, a free node cannot be added to another graph.  If the allocation is freed
 * in another graph, a free node can no longer be added to the owning graph.
 *
 * The following restrictions apply to graphs which contain allocation and/or memory free nodes:
 * - Nodes and edges of the graph cannot be deleted.
 * - The graph can only be used in a child node if the ownership is moved to the parent.
 * - Only one instantiation of the graph may exist at any point in time.
 * - The graph cannot be cloned.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorOutOfMemory
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphAddMemFreeNode,
 * ::cudaGraphMemAllocNodeGetParams,
 * ::cudaDeviceGraphMemTrim,
 * ::cudaDeviceGetGraphMemAttribute,
 * ::cudaDeviceSetGraphMemAttribute,
 * ::cudaMallocAsync,
 * ::cudaFreeAsync,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphAddExternalSemaphoresSignalNode,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemAllocNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, struct cudaMemAllocNodeParams *nodeParams);
#endif

/**
 * \brief Returns a memory alloc node's parameters
 *
 * Returns the parameters of a memory alloc node \p hNode in \p params_out.
 * The \p poolProps and \p accessDescs returned in \p params_out, are owned by the
 * node.  This memory remains valid until the node is destroyed.  The returned
 * parameters must not be modified.
 *
 * \param node       - Node to get the parameters for
 * \param params_out - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaGraphAddMemAllocNode,
 * ::cudaGraphMemFreeNodeGetParams
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaGraphMemAllocNodeGetParams(cudaGraphNode_t node, struct cudaMemAllocNodeParams *params_out);
#endif

/**
 * \brief Creates a memory free node and adds it to a graph
 *
 * Creates a new memory free node and adds it to \p graph with \p numDependencies
 * dependencies specified via \p pDependencies and address specified in \p dptr.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p pDependencies may not have any duplicate entries. A handle
 * to the new node will be returned in \p pGraphNode.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param dptr            - Address of memory to free
 *
 * ::cudaGraphAddMemFreeNode will return ::cudaErrorInvalidValue if the user attempts to free:
 * - an allocation twice in the same graph.
 * - an address that was not returned by an allocation node.
 * - an invalid address.
 *
 * The following restrictions apply to graphs which contain allocation and/or memory free nodes:
 * - Nodes and edges of the graph cannot be deleted.
 * - The graph can only be used in a child node if the ownership is moved to the parent.
 * - Only one instantiation of the graph may exist at any point in time.
 * - The graph cannot be cloned.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorNotSupported,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorOutOfMemory
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphAddMemAllocNode,
 * ::cudaGraphMemFreeNodeGetParams,
 * ::cudaDeviceGraphMemTrim,
 * ::cudaDeviceGetGraphMemAttribute,
 * ::cudaDeviceSetGraphMemAttribute,
 * ::cudaMallocAsync,
 * ::cudaFreeAsync,
 * ::cudaGraphCreate,
 * ::cudaGraphDestroyNode,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphAddExternalSemaphoresSignalNode,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemFreeNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, void *dptr);
#endif

/**
 * \brief Returns a memory free node's parameters
 *
 * Returns the address of a memory free node \p hNode in \p dptr_out.
 *
 * \param node     - Node to get the parameters for
 * \param dptr_out - Pointer to return the device address
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaGraphAddMemFreeNode,
 * ::cudaGraphMemFreeNodeGetParams
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaGraphMemFreeNodeGetParams(cudaGraphNode_t node, void *dptr_out);
#endif

/**
 * \brief Free unused memory that was cached on the specified device for use with graphs back to the OS.
 *
 * Blocks which are not in use by a graph that is either currently executing or scheduled to execute are
 * freed back to the operating system.
 *
 * \param device - The device for which cached memory should be freed.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddMemAllocNode,
 * ::cudaGraphAddMemFreeNode,
 * ::cudaDeviceGetGraphMemAttribute,
 * ::cudaDeviceSetGraphMemAttribute,
 * ::cudaMallocAsync,
 * ::cudaFreeAsync
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaDeviceGraphMemTrim(int device);
#endif

/**
 * \brief Query asynchronous allocation attributes related to graphs
 *
 * Valid attributes are:
 *
 * - ::cudaGraphMemAttrUsedMemCurrent: Amount of memory, in bytes, currently associated with graphs
 * - ::cudaGraphMemAttrUsedMemHigh: High watermark of memory, in bytes, associated with graphs since the
 *   last time it was reset.  High watermark can only be reset to zero.
 * - ::cudaGraphMemAttrReservedMemCurrent: Amount of memory, in bytes, currently allocated for use by
 *   the CUDA graphs asynchronous allocator.
 * - ::cudaGraphMemAttrReservedMemHigh: High watermark of memory, in bytes, currently allocated for use by
 *   the CUDA graphs asynchronous allocator.
 *
 * \param device - Specifies the scope of the query
 * \param attr - attribute to get
 * \param value - retrieved value
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceSetGraphMemAttribute,
 * ::cudaGraphAddMemAllocNode,
 * ::cudaGraphAddMemFreeNode,
 * ::cudaDeviceGraphMemTrim,
 * ::cudaMallocAsync,
 * ::cudaFreeAsync
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetGraphMemAttribute(int device, enum cudaGraphMemAttributeType attr, void* value);
#endif

/**
 * \brief Set asynchronous allocation attributes related to graphs
 *
 * Valid attributes are:
 *
 * - ::cudaGraphMemAttrUsedMemHigh: High watermark of memory, in bytes, associated with graphs since the
 *   last time it was reset.  High watermark can only be reset to zero.
 * - ::cudaGraphMemAttrReservedMemHigh: High watermark of memory, in bytes, currently allocated for use by
 *   the CUDA graphs asynchronous allocator.
 *
 * \param device - Specifies the scope of the query
 * \param attr - attribute to get
 * \param value - pointer to value to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDevice
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaDeviceGetGraphMemAttribute,
 * ::cudaGraphAddMemAllocNode,
 * ::cudaGraphAddMemFreeNode,
 * ::cudaDeviceGraphMemTrim,
 * ::cudaMallocAsync,
 * ::cudaFreeAsync
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaDeviceSetGraphMemAttribute(int device, enum cudaGraphMemAttributeType attr, void* value);
#endif

/**
 * \brief Clones a graph
 *
 * This function creates a copy of \p originalGraph and returns it in \p pGraphClone.
 * All parameters are copied into the cloned graph. The original graph may be modified 
 * after this call without affecting the clone.
 *
 * Child graph nodes in the original graph are recursively copied into the clone.
 *
 * \note: Cloning is not supported for graphs which contain memory allocation nodes,
 *        memory free nodes, or conditional nodes.
 *
 * \param pGraphClone  - Returns newly created cloned graph
 * \param originalGraph - Graph to clone
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphCreate,
 * ::cudaGraphNodeFindInClone
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphClone(cudaGraph_t *pGraphClone, cudaGraph_t originalGraph);

/**
 * \brief Finds a cloned version of a node
 *
 * This function returns the node in \p clonedGraph corresponding to \p originalNode 
 * in the original graph.
 *
 * \p clonedGraph must have been cloned from \p originalGraph via ::cudaGraphClone. 
 * \p originalNode must have been in \p originalGraph at the time of the call to 
 * ::cudaGraphClone, and the corresponding cloned node in \p clonedGraph must not have 
 * been removed. The cloned node is then returned via \p pClonedNode.
 *
 * \param pNode  - Returns handle to the cloned node
 * \param originalNode - Handle to the original node
 * \param clonedGraph - Cloned graph to query
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphClone
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeFindInClone(cudaGraphNode_t *pNode, cudaGraphNode_t originalNode, cudaGraph_t clonedGraph);

/**
 * \brief Returns a node's type
 *
 * Returns the node type of \p node in \p pType.
 *
 * \param node - Node to query
 * \param pType  - Pointer to return the node type
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphGetRootNodes,
 * ::cudaGraphChildGraphNodeGetGraph,
 * ::cudaGraphKernelNodeGetParams,
 * ::cudaGraphKernelNodeSetParams,
 * ::cudaGraphHostNodeGetParams,
 * ::cudaGraphHostNodeSetParams,
 * ::cudaGraphMemcpyNodeGetParams,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemsetNodeGetParams,
 * ::cudaGraphMemsetNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetType(cudaGraphNode_t node, enum cudaGraphNodeType *pType);

/**
 * \brief Returns the graph that contains a given graph node
 *
 * Returns the graph that contains \p hNode in \p *phGraph.
 * If hNode is in a child graph, the child graph it is in is returned.
 *
 * \param hNode - Node to query
 * \param phGraph - Pointer to return the containing graph
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphDebugDotPrint
 * ::cudaGraphNodeGetLocalId
 * ::cudaGraphNodeGetToolsId
 * ::cudaGraphGetId
 * ::cudaGraphExecGetId
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetContainingGraph(cudaGraphNode_t hNode, cudaGraph_t *phGraph);

/**
 * \brief Returns the node id of a given graph node
 *
 * Returns the node id of \p hNode in \p *nodeId.
 * The nodeId matches that referenced by ::cudaGraphDebugDotPrint.
 * The local nodeId and graphId together can uniquely identify the node.
 *
 * \param hNode - Node to query
 * \param nodeId - Pointer to return the nodeId 
 * \return
 * ::cudaSuccess
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphDebugDotPrint
 * ::cudaGraphNodeGetContainingGraph
 * ::cudaGraphNodeGetToolsId
 * ::cudaGraphGetId
 * ::cudaGraphExecGetId
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetLocalId(cudaGraphNode_t hNode, unsigned int *nodeId);

/**
 * \brief Returns an id used by tools to identify a given node 
 *
 * \param hNode - Node to query
 * \param *toolsNodeId - Pointer to return the id used by tools 
 * \return
 * ::CUDA_SUCCESS
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphDebugDotPrint
 * ::cudaGraphNodeGetContainingGraph
 * ::cudaGraphNodeGetLocalId
 * ::cudaGraphGetId
 * ::cudaGraphExecGetId

 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetToolsId(cudaGraphNode_t hNode, unsigned long long *toolsNodeId);

/**
 * \brief Returns the id of a given graph
 *
 * Returns the id of \p hGraph in \p *graphId.
 * The value in \p *graphId matches that referenced by ::cudaGraphDebugDotPrint.
 *
 * \param hGraph - Graph to query
 * \param graphId - Pointer to return the graphId 
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphDebugDotPrint
 * ::cudaGraphNodeGetContainingGraph
 * ::cudaGraphNodeGetLocalId
 * ::cudaGraphNodeGetToolsId
 * ::cudaGraphExecGetId
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphGetId(cudaGraph_t hGraph, unsigned int *graphID);

/**
 * \brief Returns the id of a given graph exec
 *
 * Returns the id of \p hGraphExec in \p *graphId.
 * The value in \p *graphId matches that referenced by ::cudaGraphDebugDotPrint.
 *
 * \param hGraphExec - Graph to query
 * \param graphId - Pointer to return the graphId 
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphDebugDotPrint
 * ::cudaGraphNodeGetContainingGraph
 * ::cudaGraphNodeGetLocalId
 * ::cudaGraphNodeGetToolsId
 * ::cudaGraphGetId
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecGetId(cudaGraphExec_t hGraphExec, unsigned int *graphID);

/**
 * \brief Returns a graph's nodes
 *
 * Returns a list of \p graph's nodes. \p nodes may be NULL, in which case this
 * function will return the number of nodes in \p numNodes. Otherwise,
 * \p numNodes entries will be filled in. If \p numNodes is higher than the actual
 * number of nodes, the remaining entries in \p nodes will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p numNodes.
 *
 * \param graph    - Graph to query
 * \param nodes    - Pointer to return the nodes
 * \param numNodes - See description
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphCreate,
 * ::cudaGraphGetRootNodes,
 * ::cudaGraphGetEdges,
 * ::cudaGraphNodeGetType,
 * ::cudaGraphNodeGetDependencies,
 * ::cudaGraphNodeGetDependentNodes
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphGetNodes(cudaGraph_t graph, cudaGraphNode_t *nodes, size_t *numNodes);

/**
 * \brief Returns a graph's root nodes
 *
 * Returns a list of \p graph's root nodes. \p pRootNodes may be NULL, in which case this
 * function will return the number of root nodes in \p pNumRootNodes. Otherwise,
 * \p pNumRootNodes entries will be filled in. If \p pNumRootNodes is higher than the actual
 * number of root nodes, the remaining entries in \p pRootNodes will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p pNumRootNodes.
 *
 * \param graph       - Graph to query
 * \param pRootNodes    - Pointer to return the root nodes
 * \param pNumRootNodes - See description
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphCreate,
 * ::cudaGraphGetNodes,
 * ::cudaGraphGetEdges,
 * ::cudaGraphNodeGetType,
 * ::cudaGraphNodeGetDependencies,
 * ::cudaGraphNodeGetDependentNodes
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphGetRootNodes(cudaGraph_t graph, cudaGraphNode_t *pRootNodes, size_t *pNumRootNodes);


/**
 * \brief Returns a graph's dependency edges
 *
 * Returns a list of \p graph's dependency edges. Edges are returned via corresponding
 * indices in \p from, \p to and \p edgeData; that is, the node in \p to[i] has a
 * dependency on the node in \p from[i] with data \p edgeData[i]. \p from and \p to may
 * both be NULL, in which case this function only returns the number of edges in
 * \p numEdges. Otherwise, \p numEdges entries will be filled in. If \p numEdges is higher
 * than the actual number of edges, the remaining entries in \p from and \p to will be
 * set to NULL, and the number of edges actually returned will be written to \p numEdges.
 * \p edgeData may alone be NULL, in which case the edges must all have default (zeroed)
 * edge data. Attempting a losst query via NULL \p edgeData will result in
 * ::cudaErrorLossyQuery. If \p edgeData is non-NULL then \p from and \p to must be as
 * well.
 *
 * \param graph    - Graph to get the edges from
 * \param from     - Location to return edge endpoints
 * \param to       - Location to return edge endpoints
 * \param edgeData - Optional location to return edge data
 * \param numEdges - See description
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorLossyQuery,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphGetNodes,
 * ::cudaGraphGetRootNodes,
 * ::cudaGraphAddDependencies,
 * ::cudaGraphRemoveDependencies,
 * ::cudaGraphNodeGetDependencies,
 * ::cudaGraphNodeGetDependentNodes
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphGetEdges(cudaGraph_t graph, cudaGraphNode_t *from, cudaGraphNode_t *to, cudaGraphEdgeData *edgeData, size_t *numEdges);


/**
 * \brief Returns a node's dependencies
 *
 * Returns a list of \p node's dependencies. \p pDependencies may be NULL, in which case this
 * function will return the number of dependencies in \p pNumDependencies. Otherwise,
 * \p pNumDependencies entries will be filled in. If \p pNumDependencies is higher than the actual
 * number of dependencies, the remaining entries in \p pDependencies will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p pNumDependencies.
 *
 * Note that if an edge has non-zero (non-default) edge data and \p edgeData is NULL,
 * this API will return ::cudaErrorLossyQuery. If \p edgeData is non-NULL, then
 * \p pDependencies must be as well.
 *
 * \param node             - Node to query
 * \param pDependencies    - Pointer to return the dependencies
 * \param edgeData         - Optional array to return edge data for each dependency
 * \param pNumDependencies - See description
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorLossyQuery,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetDependentNodes,
 * ::cudaGraphGetNodes,
 * ::cudaGraphGetRootNodes,
 * ::cudaGraphGetEdges,
 * ::cudaGraphAddDependencies,
 * ::cudaGraphRemoveDependencies
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetDependencies(cudaGraphNode_t node, cudaGraphNode_t *pDependencies, cudaGraphEdgeData *edgeData, size_t *pNumDependencies);


/**
 * \brief Returns a node's dependent nodes
 *
 * Returns a list of \p node's dependent nodes. \p pDependentNodes may be NULL, in which
 * case this function will return the number of dependent nodes in \p pNumDependentNodes.
 * Otherwise, \p pNumDependentNodes entries will be filled in. If \p pNumDependentNodes is
 * higher than the actual number of dependent nodes, the remaining entries in
 * \p pDependentNodes will be set to NULL, and the number of nodes actually obtained will
 * be returned in \p pNumDependentNodes.
 *
 * Note that if an edge has non-zero (non-default) edge data and \p edgeData is NULL,
 * this API will return ::cudaErrorLossyQuery. If \p edgeData is non-NULL, then
 * \p pDependentNodes must be as well.
 *
 * \param node               - Node to query
 * \param pDependentNodes    - Pointer to return the dependent nodes
 * \param edgeData           - Optional pointer to return edge data for dependent nodes
 * \param pNumDependentNodes - See description
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorLossyQuery,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetDependencies,
 * ::cudaGraphGetNodes,
 * ::cudaGraphGetRootNodes,
 * ::cudaGraphGetEdges,
 * ::cudaGraphAddDependencies,
 * ::cudaGraphRemoveDependencies
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetDependentNodes(cudaGraphNode_t node, cudaGraphNode_t *pDependentNodes, cudaGraphEdgeData *edgeData, size_t *pNumDependentNodes);


/**
 * \brief Adds dependency edges to a graph.
 *
 * The number of dependencies to be added is defined by \p numDependencies
 * Elements in \p pFrom and \p pTo at corresponding indices define a dependency.
 * Each node in \p pFrom and \p pTo must belong to \p graph.
 *
 * If \p numDependencies is 0, elements in \p pFrom and \p pTo will be ignored.
 * Specifying an existing dependency will return an error.
 *
 * \param graph - Graph to which dependencies are added
 * \param from - Array of nodes that provide the dependencies
 * \param to - Array of dependent nodes
 * \param edgeData - Optional array of edge data. If NULL, default (zeroed) edge data is assumed.
 * \param numDependencies - Number of dependencies to be added
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphRemoveDependencies,
 * ::cudaGraphGetEdges,
 * ::cudaGraphNodeGetDependencies,
 * ::cudaGraphNodeGetDependentNodes
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddDependencies(cudaGraph_t graph, const cudaGraphNode_t *from, const cudaGraphNode_t *to, const cudaGraphEdgeData *edgeData, size_t numDependencies);


/**
 * \brief Removes dependency edges from a graph.
 *
 * The number of \p pDependencies to be removed is defined by \p numDependencies.
 * Elements in \p pFrom and \p pTo at corresponding indices define a dependency.
 * Each node in \p pFrom and \p pTo must belong to \p graph.
 *
 * If \p numDependencies is 0, elements in \p pFrom and \p pTo will be ignored.
 * Specifying an edge that does not exist in the graph, with data matching
 * \p edgeData, results in an error. \p edgeData is nullable, which is equivalent
 * to passing default (zeroed) data for each edge.
 *
 * \param graph - Graph from which to remove dependencies
 * \param from - Array of nodes that provide the dependencies
 * \param to - Array of dependent nodes
 * \param edgeData - Optional array of edge data. If NULL, edge data is assumed to
 *                   be default (zeroed).
 * \param numDependencies - Number of dependencies to be removed
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddDependencies,
 * ::cudaGraphGetEdges,
 * ::cudaGraphNodeGetDependencies,
 * ::cudaGraphNodeGetDependentNodes
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphRemoveDependencies(cudaGraph_t graph, const cudaGraphNode_t *from, const cudaGraphNode_t *to, const cudaGraphEdgeData *edgeData, size_t numDependencies);

/**
 * \brief Remove a node from the graph
 *
 * Removes \p node from its graph. This operation also severs any dependencies of other nodes 
 * on \p node and vice versa.
 *
 * Dependencies cannot be removed from graphs which contain allocation or free nodes.
 * Any attempt to do so will return an error.
 *
 * \param node  - Node to remove
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphAddEmptyNode,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemsetNode
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphDestroyNode(cudaGraphNode_t node);

/**
 * \brief Creates an executable graph from a graph
 *
 * Instantiates \p graph as an executable graph. The graph is validated for any
 * structural constraints or intra-node constraints which were not previously
 * validated. If instantiation is successful, a handle to the instantiated graph
 * is returned in \p pGraphExec.
 *
 * The \p flags parameter controls the behavior of instantiation and subsequent
 * graph launches.  Valid flags are:
 *
 * - ::cudaGraphInstantiateFlagAutoFreeOnLaunch, which configures a
 * graph containing memory allocation nodes to automatically free any
 * unfreed memory allocations before the graph is relaunched.
 *
 * - ::cudaGraphInstantiateFlagDeviceLaunch, which configures the graph for launch
 * from the device. If this flag is passed, the executable graph handle returned can be
 * used to launch the graph from both the host and device. This flag cannot be used in
 * conjunction with ::cudaGraphInstantiateFlagAutoFreeOnLaunch.
 *
 * - ::cudaGraphInstantiateFlagUseNodePriority, which causes the graph
 * to use the priorities from the per-node attributes rather than the priority
 * of the launch stream during execution. Note that priorities are only available
 * on kernel nodes, and are copied from stream priority during stream capture.
 *
 * If \p graph contains any allocation or free nodes, there can be at most one
 * executable graph in existence for that graph at a time. An attempt to
 * instantiate a second executable graph before destroying the first with
 * ::cudaGraphExecDestroy will result in an error.
 * The same also applies if \p graph contains any device-updatable kernel nodes.
 * 
 * Graphs instantiated for launch on the device have additional restrictions which do not
 * apply to host graphs:
 *
 * - The graph's nodes must reside on a single device.
 * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes.
 * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node.
 *   Operation-specific restrictions are outlined below.
 * - Kernel nodes:
 *   - Use of CUDA Dynamic Parallelism is not permitted.
 *   - Cooperative launches are permitted as long as MPS is not in use.
 * - Memcpy nodes:
 *   - Only copies involving device memory and/or pinned device-mapped host memory are permitted.
 *   - Copies involving CUDA arrays are not permitted.
 *   - Both operands must be accessible from the current device, and the current device must
 *     match the device of other nodes in the graph.
 *
 * If \p graph is not instantiated for launch on the device but contains kernels which
 * call device-side cudaGraphLaunch() from multiple devices, this will result in an error.
 *
 * \param pGraphExec - Returns instantiated graph
 * \param graph      - Graph to instantiate
 * \param flags      - Flags to control instantiation.  See ::CUgraphInstantiate_flags.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphInstantiateWithFlags,
 * ::cudaGraphCreate,
 * ::cudaGraphUpload,
 * ::cudaGraphLaunch,
 * ::cudaGraphExecDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiate(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, unsigned long long flags __dv(0));

/**
 * \brief Creates an executable graph from a graph
 *
 * Instantiates \p graph as an executable graph. The graph is validated for any
 * structural constraints or intra-node constraints which were not previously
 * validated. If instantiation is successful, a handle to the instantiated graph
 * is returned in \p pGraphExec.
 *
 * The \p flags parameter controls the behavior of instantiation and subsequent
 * graph launches.  Valid flags are:
 *
 * - ::cudaGraphInstantiateFlagAutoFreeOnLaunch, which configures a
 * graph containing memory allocation nodes to automatically free any
 * unfreed memory allocations before the graph is relaunched.
 *
 * - ::cudaGraphInstantiateFlagDeviceLaunch, which configures the graph for launch
 * from the device. If this flag is passed, the executable graph handle returned can be
 * used to launch the graph from both the host and device. This flag can only be used
 * on platforms which support unified addressing. This flag cannot be used in
 * conjunction with ::cudaGraphInstantiateFlagAutoFreeOnLaunch.
 *
 * - ::cudaGraphInstantiateFlagUseNodePriority, which causes the graph
 * to use the priorities from the per-node attributes rather than the priority
 * of the launch stream during execution. Note that priorities are only available
 * on kernel nodes, and are copied from stream priority during stream capture.
 *
 * If \p graph contains any allocation or free nodes, there can be at most one
 * executable graph in existence for that graph at a time. An attempt to
 * instantiate a second executable graph before destroying the first with
 * ::cudaGraphExecDestroy will result in an error.
 * The same also applies if \p graph contains any device-updatable kernel nodes.
 *
 * If \p graph contains kernels which call device-side cudaGraphLaunch() from multiple
 * devices, this will result in an error.
 *
 * Graphs instantiated for launch on the device have additional restrictions which do not
 * apply to host graphs:
 *
 * - The graph's nodes must reside on a single device.
 * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes.
 * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node.
 *   Operation-specific restrictions are outlined below.
 * - Kernel nodes:
 *   - Use of CUDA Dynamic Parallelism is not permitted.
 *   - Cooperative launches are permitted as long as MPS is not in use.
 * - Memcpy nodes:
 *   - Only copies involving device memory and/or pinned device-mapped host memory are permitted.
 *   - Copies involving CUDA arrays are not permitted.
 *   - Both operands must be accessible from the current device, and the current device must
 *     match the device of other nodes in the graph.
 *
 * \param pGraphExec - Returns instantiated graph
 * \param graph      - Graph to instantiate
 * \param flags      - Flags to control instantiation.  See ::CUgraphInstantiate_flags.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphInstantiate,
 * ::cudaGraphCreate,
 * ::cudaGraphUpload,
 * ::cudaGraphLaunch,
 * ::cudaGraphExecDestroy
 */
#if __CUDART_API_VERSION >= 11040
extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiateWithFlags(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, unsigned long long flags __dv(0));
#endif

/**
 * \brief Creates an executable graph from a graph
 *
 * Instantiates \p graph as an executable graph according to the \p instantiateParams structure.
 * The graph is validated for any structural constraints or intra-node constraints
 * which were not previously validated. If instantiation is successful, a handle to
 * the instantiated graph is returned in \p pGraphExec.
 *
 * \p instantiateParams controls the behavior of instantiation and subsequent
 * graph launches, as well as returning more detailed information in the event of an error.
 * ::cudaGraphInstantiateParams is defined as:
 *
 * \code
    typedef struct {
        unsigned long long flags;
        cudaStream_t uploadStream;
        cudaGraphNode_t errNode_out;
        cudaGraphInstantiateResult result_out;
    } cudaGraphInstantiateParams;
 * \endcode
 *
 * The \p flags field controls the behavior of instantiation and subsequent
 * graph launches. Valid flags are:
 *
 * - ::cudaGraphInstantiateFlagAutoFreeOnLaunch, which configures a
 * graph containing memory allocation nodes to automatically free any
 * unfreed memory allocations before the graph is relaunched.
 *
 * - ::cudaGraphInstantiateFlagUpload, which will perform an upload of the graph
 * into \p uploadStream once the graph has been instantiated.
 *
 * - ::cudaGraphInstantiateFlagDeviceLaunch, which configures the graph for launch
 * from the device. If this flag is passed, the executable graph handle returned can be
 * used to launch the graph from both the host and device. This flag can only be used
 * on platforms which support unified addressing. This flag cannot be used in
 * conjunction with ::cudaGraphInstantiateFlagAutoFreeOnLaunch.
 *
 * - ::cudaGraphInstantiateFlagUseNodePriority, which causes the graph
 * to use the priorities from the per-node attributes rather than the priority
 * of the launch stream during execution. Note that priorities are only available
 * on kernel nodes, and are copied from stream priority during stream capture.
 *
 * If \p graph contains any allocation or free nodes, there can be at most one
 * executable graph in existence for that graph at a time. An attempt to instantiate a
 * second executable graph before destroying the first with ::cudaGraphExecDestroy will
 * result in an error.
 * The same also applies if \p graph contains any device-updatable kernel nodes.
 *
 * If \p graph contains kernels which call device-side cudaGraphLaunch() from multiple
 * devices, this will result in an error.
 *
 * Graphs instantiated for launch on the device have additional restrictions which do not
 * apply to host graphs:
 *
 * - The graph's nodes must reside on a single device.
 * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes.
 * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node.
 *   Operation-specific restrictions are outlined below.
 * - Kernel nodes:
 *   - Use of CUDA Dynamic Parallelism is not permitted.
 *   - Cooperative launches are permitted as long as MPS is not in use.
 * - Memcpy nodes:
 *   - Only copies involving device memory and/or pinned device-mapped host memory are permitted.
 *   - Copies involving CUDA arrays are not permitted.
 *   - Both operands must be accessible from the current device, and the current device must
 *     match the device of other nodes in the graph.
 *
 * In the event of an error, the \p result_out and \p errNode_out fields will contain more
 * information about the nature of the error. Possible error reporting includes:
 *
 * - ::cudaGraphInstantiateError, if passed an invalid value or if an unexpected error occurred
 *   which is described by the return value of the function. \p errNode_out will be set to NULL.
 * - ::cudaGraphInstantiateInvalidStructure, if the graph structure is invalid. \p errNode_out
 *   will be set to one of the offending nodes.
 * - ::cudaGraphInstantiateNodeOperationNotSupported, if the graph is instantiated for device
 *   launch but contains a node of an unsupported node type, or a node which performs unsupported
 *   operations, such as use of CUDA dynamic parallelism within a kernel node. \p errNode_out will
 *   be set to this node.
 * - ::cudaGraphInstantiateMultipleDevicesNotSupported, if the graph is instantiated for device
 *   launch but a node’s device differs from that of another node. This error can also be returned
 *   if a graph is not instantiated for device launch and it contains kernels which call device-side
 *   cudaGraphLaunch() from multiple devices. \p errNode_out will be set to this node.
 *
 * If instantiation is successful, \p result_out will be set to ::cudaGraphInstantiateSuccess,
 * and \p hErrNode_out will be set to NULL.
 *
 * \param pGraphExec       - Returns instantiated graph
 * \param graph            - Graph to instantiate
 * \param instantiateParams - Instantiation parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphCreate,
 * ::cudaGraphInstantiate,
 * ::cudaGraphInstantiateWithFlags,
 * ::cudaGraphExecDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiateWithParams(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, cudaGraphInstantiateParams *instantiateParams);

/**
 * \brief Query the instantiation flags of an executable graph
 *
 * Returns the flags that were passed to instantiation for the given executable graph.
 * ::cudaGraphInstantiateFlagUpload will not be returned by this API as it does
 * not affect the resulting executable graph.
 *
 * \param graphExec - The executable graph to query
 * \param flags     - Returns the instantiation flags
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphInstantiate,
 * ::cudaGraphInstantiateWithFlags,
 * ::cudaGraphInstantiateWithParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecGetFlags(cudaGraphExec_t graphExec, unsigned long long *flags);

/**
 * \brief Sets the parameters for a kernel node in the given graphExec
 *
 * Sets the parameters of a kernel node in an executable graph \p hGraphExec. 
 * The node is identified by the corresponding node \p node in the 
 * non-executable graph, from which the executable graph was instantiated. 
 *
 * \p node must not have been removed from the original graph. All \p nodeParams 
 * fields may change, but the following restrictions apply to \p func updates: 
 *
 *   - The owning device of the function cannot change.
 *   - A node whose function originally did not use CUDA dynamic parallelism cannot be updated
 *     to a function which uses CDP
 *   - A node whose function originally did not make device-side update calls cannot be updated
 *     to a function which makes device-side update calls.
 *   - If \p hGraphExec was not instantiated for device launch, a node whose function originally
 *     did not use device-side cudaGraphLaunch() cannot be updated to a function which uses
 *     device-side cudaGraphLaunch() unless the node resides on the same device as nodes which
 *     contained such calls at instantiate-time. If no such calls were present at instantiation,
 *     these updates cannot be performed at all.
 *
 * The modifications only affect future launches of \p hGraphExec. Already 
 * enqueued or running launches of \p hGraphExec are not affected by this call. 
 * \p node is also not modified by this call.
 *
 * If \p node is a device-updatable kernel node, the next upload/launch of \p hGraphExec
 * will overwrite any previous device-side updates. Additionally, applying host updates to a
 * device-updatable kernel node while it is being updated from the device will result in
 * undefined behavior.
 *
 * \param hGraphExec  - The executable graph in which to set the specified node
 * \param node        - kernel node from the graph from which graphExec was instantiated
 * \param pNodeParams - Updated Parameters to set
 * 
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_cudaKernel_t
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddKernelNode,
 * ::cudaGraphKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecKernelNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaKernelNodeParams *pNodeParams);

/**
 * \brief Sets the parameters for a memcpy node in the given graphExec.
 *
 * Updates the work represented by \p node in \p hGraphExec as though \p node had 
 * contained \p pNodeParams at instantiation.  \p node must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from \p node are ignored.
 *
 * The source and destination memory in \p pNodeParams must be allocated from the same 
 * contexts as the original source and destination memory.  Both the instantiation-time 
 * memory operands and the memory operands in \p pNodeParams must be 1-dimensional.
 * Zero-length operations are not supported.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also 
 * not modified by this call.
 *
 * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or
 * either the original or new memory operands are multidimensional.
 *
 * \param hGraphExec  - The executable graph in which to set the specified node
 * \param node        - Memcpy node from the graph which was used to instantiate graphExec
 * \param pNodeParams - Updated Parameters to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphExecMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphExecMemcpyNodeSetParams1D,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaMemcpy3DParms *pNodeParams);

/**
 * \brief Sets the parameters for a memcpy node in the given graphExec to copy to a symbol on the device
 *
 * Updates the work represented by \p node in \p hGraphExec as though \p node had 
 * contained the given params at instantiation.  \p node must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from \p node are ignored.
 *
 * \p src and \p symbol must be allocated from the same contexts as the original source and
 * destination memory.  The instantiation-time memory operands must be 1-dimensional.
 * Zero-length operations are not supported.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also 
 * not modified by this call.
 *
 * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or
 * the original memory operands are multidimensional.
 *
 * \param hGraphExec      - The executable graph in which to set the specified node
 * \param node            - Memcpy node from the graph which was used to instantiate graphExec
 * \param symbol          - Device symbol address
 * \param src             - Source memory address
 * \param count           - Size in bytes to copy
 * \param offset          - Offset from start of symbol in bytes
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemcpyNodeToSymbol,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParamsToSymbol(
    cudaGraphExec_t hGraphExec,
    cudaGraphNode_t node,
    const void* symbol,
    const void* src,
    size_t count,
    size_t offset,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Sets the parameters for a memcpy node in the given graphExec to copy from a symbol on the device
 *
 * Updates the work represented by \p node in \p hGraphExec as though \p node had 
 * contained the given params at instantiation.  \p node must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from \p node are ignored.
 *
 * \p symbol and \p dst must be allocated from the same contexts as the original source and
 * destination memory.  The instantiation-time memory operands must be 1-dimensional.
 * Zero-length operations are not supported.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also 
 * not modified by this call.
 *
 * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or
 * the original memory operands are multidimensional.
 *
 * \param hGraphExec      - The executable graph in which to set the specified node
 * \param node            - Memcpy node from the graph which was used to instantiate graphExec
 * \param dst             - Destination memory address
 * \param symbol          - Device symbol address
 * \param count           - Size in bytes to copy
 * \param offset          - Offset from start of symbol in bytes
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemcpyNodeFromSymbol,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParamsFromSymbol,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParamsToSymbol,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParamsFromSymbol(
    cudaGraphExec_t hGraphExec,
    cudaGraphNode_t node,
    void* dst,
    const void* symbol,
    size_t count,
    size_t offset,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Sets the parameters for a memcpy node in the given graphExec to perform a 1-dimensional copy
 *
 * Updates the work represented by \p node in \p hGraphExec as though \p node had 
 * contained the given params at instantiation.  \p node must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from \p node are ignored.
 *
 * \p src and \p dst must be allocated from the same contexts as the original source
 * and destination memory.  The instantiation-time memory operands must be 1-dimensional.
 * Zero-length operations are not supported.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also 
 * not modified by this call.
 *
 * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or
 * the original memory operands are multidimensional.
 *
 * \param hGraphExec      - The executable graph in which to set the specified node
 * \param node            - Memcpy node from the graph which was used to instantiate graphExec
 * \param dst             - Destination memory address
 * \param src             - Source memory address
 * \param count           - Size in bytes to copy
 * \param kind            - Type of transfer
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddMemcpyNode,
 * ::cudaGraphAddMemcpyNode1D,
 * ::cudaGraphMemcpyNodeSetParams,
 * ::cudaGraphMemcpyNodeSetParams1D,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParams1D(
    cudaGraphExec_t hGraphExec,
    cudaGraphNode_t node,
    void* dst,
    const void* src,
    size_t count,
    enum cudaMemcpyKind kind);
#endif

/**
 * \brief Sets the parameters for a memset node in the given graphExec.
 *
 * Updates the work represented by \p node in \p hGraphExec as though \p node had 
 * contained \p pNodeParams at instantiation.  \p node must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from \p node are ignored.
 *
 * Zero sized operations are not supported.
 *
 * The new destination pointer in \p pNodeParams must be to the same kind of allocation
 * as the original destination pointer and have the same context association and device mapping
 * as the original destination pointer.
 *
 * Both the value and pointer address may be updated.  
 * Changing other aspects of the memset (width, height, element size or pitch) may cause the update to be rejected.
 * Specifically, for 2d memsets, all dimension changes are rejected.
 * For 1d memsets, changes in height are explicitly rejected and other changes are opportunistically allowed
 * if the resulting work maps onto the work resources already allocated for the node.

 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also 
 * not modified by this call.
 *
 * \param hGraphExec  - The executable graph in which to set the specified node
 * \param node        - Memset node from the graph which was used to instantiate graphExec
 * \param pNodeParams - Updated Parameters to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddMemsetNode,
 * ::cudaGraphMemsetNodeSetParams,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemsetNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaMemsetParams *pNodeParams);

/**
 * \brief Sets the parameters for a host node in the given graphExec.
 *
 * Updates the work represented by \p node in \p hGraphExec as though \p node had 
 * contained \p pNodeParams at instantiation.  \p node must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from \p node are ignored.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also 
 * not modified by this call.
 *
 * \param hGraphExec  - The executable graph in which to set the specified node
 * \param node        - Host node from the graph which was used to instantiate graphExec
 * \param pNodeParams - Updated Parameters to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddHostNode,
 * ::cudaGraphHostNodeSetParams,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecHostNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaHostNodeParams *pNodeParams);

/**
 * \brief Updates node parameters in the child graph node in the given graphExec.
 *
 * Updates the work represented by \p node in \p hGraphExec as though the nodes contained
 * in \p node's graph had the parameters contained in \p childGraph's nodes at instantiation.
 * \p node must remain in the graph which was used to instantiate \p hGraphExec.
 * Changed edges to and from \p node are ignored.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued
 * or running launches of \p hGraphExec are not affected by this call.  \p node is also
 * not modified by this call.
 *
 * The topology of \p childGraph, as well as the node insertion order,  must match that
 * of the graph contained in \p node.  See ::cudaGraphExecUpdate() for a list of restrictions
 * on what can be updated in an instantiated graph.  The update is recursive, so child graph
 * nodes contained within the top level child graph will also be updated.

 * \param hGraphExec - The executable graph in which to set the specified node
 * \param node       - Host node from the graph which was used to instantiate graphExec
 * \param childGraph - The graph supplying the updated parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddChildGraphNode,
 * ::cudaGraphChildGraphNodeGetGraph,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphExecChildGraphNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, cudaGraph_t childGraph);
#endif

/**
 * \brief Sets the event for an event record node in the given graphExec
 *
 * Sets the event of an event record node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Event record node from the graph from which graphExec was instantiated
 * \param event      - Updated event to use
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddEventRecordNode,
 * ::cudaGraphEventRecordNodeGetEvent,
 * ::cudaGraphEventWaitNodeSetEvent,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphExecEventRecordNodeSetEvent(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, cudaEvent_t event);
#endif

/**
 * \brief Sets the event for an event wait node in the given graphExec
 *
 * Sets the event of an event wait node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Event wait node from the graph from which graphExec was instantiated
 * \param event      - Updated event to use
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddEventWaitNode,
 * ::cudaGraphEventWaitNodeGetEvent,
 * ::cudaGraphEventRecordNodeSetEvent,
 * ::cudaEventRecordWithFlags,
 * ::cudaStreamWaitEvent,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphExecEventWaitNodeSetEvent(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, cudaEvent_t event);
#endif

/**
 * \brief Sets the parameters for an external semaphore signal node in the given graphExec
 *
 * Sets the parameters of an external semaphore signal node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * Changing \p nodeParams->numExtSems is not supported.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - semaphore signal node from the graph from which graphExec was instantiated
 * \param nodeParams - Updated Parameters to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresSignalNode,
 * ::cudaImportExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphExecExternalSemaphoresSignalNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, const struct cudaExternalSemaphoreSignalNodeParams *nodeParams);
#endif

/**
 * \brief Sets the parameters for an external semaphore wait node in the given graphExec
 *
 * Sets the parameters of an external semaphore wait node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * Changing \p nodeParams->numExtSems is not supported.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - semaphore wait node from the graph from which graphExec was instantiated
 * \param nodeParams - Updated Parameters to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphExecNodeSetParams,
 * ::cudaGraphAddExternalSemaphoresWaitNode,
 * ::cudaImportExternalSemaphore,
 * ::cudaSignalExternalSemaphoresAsync,
 * ::cudaWaitExternalSemaphoresAsync,
 * ::cudaGraphExecKernelNodeSetParams,
 * ::cudaGraphExecMemcpyNodeSetParams,
 * ::cudaGraphExecMemsetNodeSetParams,
 * ::cudaGraphExecHostNodeSetParams,
 * ::cudaGraphExecChildGraphNodeSetParams,
 * ::cudaGraphExecEventRecordNodeSetEvent,
 * ::cudaGraphExecEventWaitNodeSetEvent,
 * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
#if __CUDART_API_VERSION >= 11020
extern __host__ cudaError_t CUDARTAPI cudaGraphExecExternalSemaphoresWaitNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, const struct cudaExternalSemaphoreWaitNodeParams *nodeParams);
#endif

/**
 * \brief Enables or disables the specified node in the given graphExec
 *
 * Sets \p hNode to be either enabled or disabled. Disabled nodes are functionally equivalent 
 * to empty nodes until they are reenabled. Existing node parameters are not affected by 
 * disabling/enabling the node.
 *  
 * The node is identified by the corresponding node \p hNode in the non-executable 
 * graph, from which the executable graph was instantiated.   
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * \note Currently only kernel, memset and memcpy nodes are supported. 
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Node from the graph from which graphExec was instantiated
 * \param isEnabled  - Node is enabled if != 0, otherwise the node is disabled
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetEnabled,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 * ::cudaGraphLaunch
 */
#if __CUDART_API_VERSION >= 11060
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeSetEnabled(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, unsigned int isEnabled);
#endif

/**
 * \brief Query whether a node in the given graphExec is enabled
 *
 * Sets isEnabled to 1 if \p hNode is enabled, or 0 if \p hNode is disabled.
 *
 * The node is identified by the corresponding node \p hNode in the non-executable 
 * graph, from which the executable graph was instantiated.   
 *
 * \p hNode must not have been removed from the original graph.
 *
 * \note Currently only kernel, memset and memcpy nodes are supported. 
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Node from the graph from which graphExec was instantiated
 * \param isEnabled  - Location to return the enabled status of the node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeSetEnabled,
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 * ::cudaGraphLaunch
 */
#if __CUDART_API_VERSION >= 11060
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetEnabled(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, unsigned int *isEnabled);
#endif

/**
 * \brief Check whether an executable graph can be updated with a graph and perform the update if possible
 *
 * Updates the node parameters in the instantiated graph specified by \p hGraphExec with the
 * node parameters in a topologically identical graph specified by \p hGraph.
 *
 * Limitations:
 *
 * - Kernel nodes:
 *   - The owning context of the function cannot change.
 *   - A node whose function originally did not use CUDA dynamic parallelism cannot be updated
 *     to a function which uses CDP.
 *   - A node whose function originally did not make device-side update calls cannot be updated
 *     to a function which makes device-side update calls.
 *   - A cooperative node cannot be updated to a non-cooperative node, and vice-versa.
 *   - If the graph was instantiated with cudaGraphInstantiateFlagUseNodePriority, the
 *     priority attribute cannot change. Equality is checked on the originally requested
 *     priority values, before they are clamped to the device's supported range.
 *   - If \p hGraphExec was not instantiated for device launch, a node whose function originally
 *     did not use device-side cudaGraphLaunch() cannot be updated to a function which uses
 *     device-side cudaGraphLaunch() unless the node resides on the same device as nodes which
 *     contained such calls at instantiate-time. If no such calls were present at instantiation,
 *     these updates cannot be performed at all.
 *   - Neither \p hGraph nor \p hGraphExec may contain device-updatable kernel nodes.
 * - Memset and memcpy nodes:
 *   - The CUDA device(s) to which the operand(s) was allocated/mapped cannot change.
 *   - The source/destination memory must be allocated from the same contexts as the original
 *     source/destination memory.
 *   - For 2d memsets, only address and assigned value may be updated.
 *   - For 1d memsets, updating dimensions is also allowed, but may fail if the resulting operation doesn't
 *     map onto the work resources already allocated for the node. 
 * - Additional memcpy node restrictions:
 *   - Changing either the source or destination memory type(i.e. CU_MEMORYTYPE_DEVICE,
 *     CU_MEMORYTYPE_ARRAY, etc.) is not supported.
 * - Conditional nodes:
 *   - Changing node parameters is not supported.
 *   - Changing parameters of nodes within the conditional body graph is subject to the rules above.
 *   - Conditional handle flags and default values are updated as part of the graph update.
 *
 * Note:  The API may add further restrictions in future releases.  The return code should always be checked.
 *
 * cudaGraphExecUpdate sets the result member of \p resultInfo to cudaGraphExecUpdateErrorTopologyChanged
 * under the following conditions:
 * - The count of nodes directly in \p hGraphExec and \p hGraph differ, in which case resultInfo->errorNode
 *   is set to NULL.
 * - \p hGraph has more exit nodes than \p hGraph, in which case resultInfo->errorNode is set to one of
 *   the exit nodes in hGraph. 
 * - A node in \p hGraph has a different number of dependencies than the node from \p hGraphExec it is paired with,
 *   in which case resultInfo->errorNode is set to the node from \p hGraph.
 * - A node in \p hGraph has a dependency that does not match with the corresponding dependency of the paired node
 *   from \p hGraphExec. resultInfo->errorNode will be set to the node from \p hGraph. resultInfo->errorFromNode
 *   will be set to the mismatched dependency. The dependencies are paired based on edge order and a dependency
 *   does not match when the nodes are already paired based on other edges examined in the graph.
 *
 * cudaGraphExecUpdate sets \p the result member of \p resultInfo to:
 * - cudaGraphExecUpdateError if passed an invalid value.
 * - cudaGraphExecUpdateErrorTopologyChanged if the graph topology changed
 * - cudaGraphExecUpdateErrorNodeTypeChanged if the type of a node changed, in which case
 *   \p hErrorNode_out is set to the node from \p hGraph.
 * - cudaGraphExecUpdateErrorFunctionChanged if the function of a kernel node changed (CUDA driver < 11.2)
 * - cudaGraphExecUpdateErrorUnsupportedFunctionChange if the func field of a kernel changed in an
 *   unsupported way(see note above), in which case \p hErrorNode_out is set to the node from \p hGraph
 * - cudaGraphExecUpdateErrorParametersChanged if any parameters to a node changed in a way 
 *   that is not supported, in which case \p hErrorNode_out is set to the node from \p hGraph
 * - cudaGraphExecUpdateErrorAttributesChanged if any attributes of a node changed in a way 
 *   that is not supported, in which case \p hErrorNode_out is set to the node from \p hGraph
 * - cudaGraphExecUpdateErrorNotSupported if something about a node is unsupported, like 
 *   the node's type or configuration, in which case \p hErrorNode_out is set to the node from \p hGraph
 *
 * If the update fails for a reason not listed above, the result member of \p resultInfo will be set
 * to cudaGraphExecUpdateError. If the update succeeds, the result member will be set to cudaGraphExecUpdateSuccess.
 *
 * cudaGraphExecUpdate returns cudaSuccess when the updated was performed successfully.  It returns
 * cudaErrorGraphExecUpdateFailure if the graph update was not performed because it included 
 * changes which violated constraints specific to instantiated graph update.
 *
 * \param hGraphExec The instantiated graph to be updated
 * \param hGraph The graph containing the updated parameters
   \param resultInfo the error info structure
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorGraphExecUpdateFailure,
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphInstantiate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecUpdate(cudaGraphExec_t hGraphExec, cudaGraph_t hGraph, cudaGraphExecUpdateResultInfo *resultInfo);

/**
 * \brief Uploads an executable graph in a stream
 *
 * Uploads \p hGraphExec to the device in \p hStream without executing it. Uploads of
 * the same \p hGraphExec will be serialized. Each upload is ordered behind both any
 * previous work in \p hStream and any previous launches of \p hGraphExec.
 * Uses memory cached by \p stream to back the allocations owned by \p graphExec.
 *
 * \param hGraphExec - Executable graph to upload
 * \param hStream    - Stream in which to upload the graph
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * \notefnerr
 * \note_init_rt
 *
 * \sa
 * ::cudaGraphInstantiate,
 * ::cudaGraphLaunch,
 * ::cudaGraphExecDestroy
 */
#if __CUDART_API_VERSION >= 11010
 extern __host__ cudaError_t CUDARTAPI cudaGraphUpload(cudaGraphExec_t graphExec, cudaStream_t stream);
#endif

/**
 * \brief Launches an executable graph in a stream
 *
 * Executes \p graphExec in \p stream. Only one instance of \p graphExec may be executing
 * at a time. Each launch is ordered behind both any previous work in \p stream
 * and any previous launches of \p graphExec. To execute a graph concurrently, it must be
 * instantiated multiple times into multiple executable graphs.
 *
 * If any allocations created by \p graphExec remain unfreed (from a previous launch) and
 * \p graphExec was not instantiated with ::cudaGraphInstantiateFlagAutoFreeOnLaunch,
 * the launch will fail with ::cudaErrorInvalidValue.
 *
 * \param graphExec - Executable graph to launch
 * \param stream    - Stream in which to launch the graph
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphInstantiate,
 * ::cudaGraphUpload,
 * ::cudaGraphExecDestroy
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphLaunch(cudaGraphExec_t graphExec, cudaStream_t stream);

/**
 * \brief Destroys an executable graph
 *
 * Destroys the executable graph specified by \p graphExec.
 *
 * \param graphExec - Executable graph to destroy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa
 * ::cudaGraphInstantiate,
 * ::cudaGraphUpload,
 * ::cudaGraphLaunch
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecDestroy(cudaGraphExec_t graphExec);

/**
 * \brief Destroys a graph
 *
 * Destroys the graph specified by \p graph, as well as all of its nodes.
 *
 * \param graph - Graph to destroy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 * \note_destroy_ub
 *
 * \sa
 * ::cudaGraphCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphDestroy(cudaGraph_t graph);

/**
 * \brief Write a DOT file describing graph structure
 *
 * Using the provided \p graph, write to \p path a DOT formatted description of the graph.
 * By default this includes the graph topology, node types, node id, kernel names and memcpy direction.
 * \p flags can be specified to write more detailed information about each node type such as
 * parameter values, kernel attributes, node and function handles.
 *
 * \param graph - The graph to create a DOT file from
 * \param path  - The path to write the DOT file to
 * \param flags - Flags from cudaGraphDebugDotFlags for specifying which additional node information to write
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorOperatingSystem
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphDebugDotPrint(cudaGraph_t graph, const char *path, unsigned int flags);

/**
 * \brief Create a user object
 *
 * Create a user object with the specified destructor callback and initial reference count. The
 * initial references are owned by the caller.
 *
 * Destructor callbacks cannot make CUDA API calls and should avoid blocking behavior, as they
 * are executed by a shared internal thread. Another thread may be signaled to perform such
 * actions, if it does not block forward progress of tasks scheduled through CUDA.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param object_out      - Location to return the user object handle
 * \param ptr             - The pointer to pass to the destroy function
 * \param destroy         - Callback to free the user object when it is no longer in use
 * \param initialRefcount - The initial refcount to create the object with, typically 1. The
 *                          initial references are owned by the calling thread.
 * \param flags           - Currently it is required to pass ::cudaUserObjectNoDestructorSync,
 *                          which is the only defined flag. This indicates that the destroy
 *                          callback cannot be waited on by any CUDA API. Users requiring
 *                          synchronization of the callback should signal its completion
 *                          manually.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaUserObjectRetain,
 * ::cudaUserObjectRelease,
 * ::cudaGraphRetainUserObject,
 * ::cudaGraphReleaseUserObject,
 * ::cudaGraphCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaUserObjectCreate(cudaUserObject_t *object_out, void *ptr, cudaHostFn_t destroy, unsigned int initialRefcount, unsigned int flags);

/**
 * \brief Retain a reference to a user object
 *
 * Retains new references to a user object. The new references are owned by the caller.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param object - The object to retain
 * \param count  - The number of references to retain, typically 1. Must be nonzero
 *                 and not larger than INT_MAX.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaUserObjectCreate,
 * ::cudaUserObjectRelease,
 * ::cudaGraphRetainUserObject,
 * ::cudaGraphReleaseUserObject,
 * ::cudaGraphCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaUserObjectRetain(cudaUserObject_t object, unsigned int count __dv(1));

/**
 * \brief Release a reference to a user object
 *
 * Releases user object references owned by the caller. The object's destructor is invoked if
 * the reference count reaches zero.
 *
 * It is undefined behavior to release references not owned by the caller, or to use a user
 * object handle after all references are released.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param object - The object to release
 * \param count  - The number of references to release, typically 1. Must be nonzero
 *                 and not larger than INT_MAX.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaUserObjectCreate,
 * ::cudaUserObjectRetain,
 * ::cudaGraphRetainUserObject,
 * ::cudaGraphReleaseUserObject,
 * ::cudaGraphCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaUserObjectRelease(cudaUserObject_t object, unsigned int count __dv(1));

/**
 * \brief Retain a reference to a user object from a graph
 *
 * Creates or moves user object references that will be owned by a CUDA graph.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param graph  - The graph to associate the reference with
 * \param object - The user object to retain a reference for
 * \param count  - The number of references to add to the graph, typically 1. Must be
 *                 nonzero and not larger than INT_MAX.
 * \param flags  - The optional flag ::cudaGraphUserObjectMove transfers references
 *                 from the calling thread, rather than create new references. Pass 0
 *                 to create new references.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaUserObjectCreate
 * ::cudaUserObjectRetain,
 * ::cudaUserObjectRelease,
 * ::cudaGraphReleaseUserObject,
 * ::cudaGraphCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphRetainUserObject(cudaGraph_t graph, cudaUserObject_t object, unsigned int count __dv(1), unsigned int flags __dv(0));

/**
 * \brief Release a user object reference from a graph
 *
 * Releases user object references owned by a graph.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param graph  - The graph that will release the reference
 * \param object - The user object to release a reference for
 * \param count  - The number of references to release, typically 1. Must be nonzero
 *                 and not larger than INT_MAX.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue
 *
 * \sa
 * ::cudaUserObjectCreate
 * ::cudaUserObjectRetain,
 * ::cudaUserObjectRelease,
 * ::cudaGraphRetainUserObject,
 * ::cudaGraphCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphReleaseUserObject(cudaGraph_t graph, cudaUserObject_t object, unsigned int count __dv(1));


/**
 * \brief Adds a node of arbitrary type to a graph
 *
 * Creates a new node in \p graph described by \p nodeParams with \p numDependencies
 * dependencies specified via \p pDependencies. \p numDependencies may be 0.
 * \p pDependencies may be null if \p numDependencies is 0. \p pDependencies may not have
 * any duplicate entries.
 *
 * \p nodeParams is a tagged union. The node type should be specified in the \p type field,
 * and type-specific parameters in the corresponding union member. All unused bytes - that
 * is, \p reserved0 and all bytes past the utilized union member - must be set to zero.
 * It is recommended to use brace initialization or memset to ensure all bytes are
 * initialized.
 *
 * Note that for some node types, \p nodeParams may contain "out parameters" which are
 * modified during the call, such as \p nodeParams->alloc.dptr.
 *
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * \param pGraphNode      - Returns newly created node
 * \param graph           - Graph to which to add the node
 * \param pDependencies   - Dependencies of the node
 * \param dependencyData  - Optional edge data for the dependencies. If NULL, the data is
 *                          assumed to be default (zeroed) for all dependencies.
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Specification of the node
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorNotSupported
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphCreate,
 * ::cudaGraphNodeSetParams,
 * ::cudaGraphExecNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphAddNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, struct cudaGraphNodeParams *nodeParams);

/**
 * \brief Update a graph node's parameters
 *
 * Sets the parameters of graph node \p node to \p nodeParams. The node type specified by
 * \p nodeParams->type must match the type of \p node. \p nodeParams must be fully
 * initialized and all unused bytes (reserved, padding) zeroed.
 *
 * Modifying parameters is not supported for node types cudaGraphNodeTypeMemAlloc and
 * cudaGraphNodeTypeMemFree.
 *
 * \param node       - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorNotSupported
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaGraphAddNode,
 * ::cudaGraphExecNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeSetParams(cudaGraphNode_t node, struct cudaGraphNodeParams *nodeParams);

/**
 * \brief Returns a graph node's parameters
 *
 * Returns the parameters of graph node \p node in \p *nodeParams.
 * 
 * Any pointers returned in \p *nodeParams point to driver-owned memory associated 
 * with the node. This memory remains valid until the node is destroyed.  Any memory
 * pointed to from \p *nodeParams must not be modified.
 *  
 * The returned parameters are a description of the node, but may not be identical to the 
 * struct provided at creation and may not be suitable for direct creation of identical 
 * nodes. This is because parameters may be partially unspecified and filled in by the 
 * driver at creation, may reference non-copyable handles, or may describe ownership 
 * semantics or other parameters that govern behavior of node creation but are not part 
 * of the final functional descriptor.
 *
 * \param node       - Node to get the parameters for
 * \param nodeParams - Pointer to return the parameters
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphNodeGetParams,
 * ::cudaGraphNodeSetParams,
 * ::cudaGraphAddNode,
 * ::cudaGraphExecNodeSetParams
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetParams(cudaGraphNode_t node, struct cudaGraphNodeParams *nodeParams);

/**
 * \brief Update a graph node's parameters in an instantiated graph
 *
 * Sets the parameters of a node in an executable graph \p graphExec. The node is identified
 * by the corresponding node \p node in the non-executable graph from which the executable
 * graph was instantiated. \p node must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p graphExec. Already
 * enqueued or running launches of \p graphExec are not affected by this call.
 * \p node is also not modified by this call.
 *
 * Allowed changes to parameters on executable graphs are as follows:
 * <table>
 *   <tr><th>Node type<th>Allowed changes
 *   <tr><td>kernel<td>See ::cudaGraphExecKernelNodeSetParams
 *   <tr><td>memcpy<td>Addresses for 1-dimensional copies if allocated in same context; see ::cudaGraphExecMemcpyNodeSetParams
 *   <tr><td>memset<td>Addresses for 1-dimensional memsets if allocated in same context; see ::cudaGraphExecMemsetNodeSetParams
 *   <tr><td>host<td>Unrestricted
 *   <tr><td>child graph<td>Topology must match and restrictions apply recursively; see ::cudaGraphExecUpdate
 *   <tr><td>event wait<td>Unrestricted
 *   <tr><td>event record<td>Unrestricted
 *   <tr><td>external semaphore signal<td>Number of semaphore operations cannot change
 *   <tr><td>external semaphore wait<td>Number of semaphore operations cannot change
 *   <tr><td>memory allocation<td>API unsupported
 *   <tr><td>memory free<td>API unsupported
 * </table>
 *
 * \param graphExec  - The executable graph in which to update the specified node
 * \param node       - Corresponding node from the graph from which graphExec was instantiated
 * \param nodeParams - Updated Parameters to set
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorNotSupported
 * \note_graph_thread_safety
 * \notefnerr
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cudaGraphAddNode,
 * ::cudaGraphNodeSetParams
 * ::cudaGraphExecUpdate,
 * ::cudaGraphInstantiate
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphExecNodeSetParams(cudaGraphExec_t graphExec, cudaGraphNode_t node, struct cudaGraphNodeParams *nodeParams);

/**
 * \brief Create a conditional handle
 *
 * Creates a conditional handle associated with \p hGraph.
 *
 * The conditional handle must be associated with a conditional node in this graph or one of its children.
 *  
 * Handles not associated with a conditional node may cause graph instantiation to fail. 
 *
 * \param pHandle_out        - Pointer used to return the handle to the caller.
 * \param graph              - Graph which will contain the conditional node using this handle.
 * \param defaultLaunchValue - Optional initial value for the conditional variable.
 *                             Applied at the beginning of each graph execution if cudaGraphCondAssignDefault is set in \p flags.
 * \param flags              - Currently must be cudaGraphCondAssignDefault or 0.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphConditionalHandleCreate(cudaGraphConditionalHandle *pHandle_out, cudaGraph_t graph, unsigned int defaultLaunchValue __dv(0), unsigned int flags __dv(0));

/**
 * \brief Create a conditional handle
 *
 * Creates a conditional handle associated with \p hGraph.
 *
 * The conditional handle must be associated with a conditional node in this graph or one of its children.
 *  
 * Handles not associated with a conditional node may cause graph instantiation to fail. 
 *
 * \param pHandle_out        - Pointer used to return the handle to the caller.
 * \param graph              - Graph which will contain the conditional node using this handle.
 * \param ctx                - Execution context for the handle and associated conditional node. If NULL, current context will be used.
 * \param defaultLaunchValue - Optional initial value for the conditional variable.
 *                             Applied at the beginning of each graph execution if cudaGraphCondAssignDefault is set in \p flags.
 * \param flags              - Currently must be cudaGraphCondAssignDefault or 0.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 */
extern __host__ cudaError_t CUDARTAPI cudaGraphConditionalHandleCreate_v2(cudaGraphConditionalHandle *pHandle_out, cudaGraph_t graph, cudaExecutionContext_t ctx __dv(NULL), unsigned int defaultLaunchValue __dv(0), unsigned int flags __dv(0));

/** @} */ /* END CUDART_GRAPH */

/**
 * \defgroup CUDART_DRIVER_ENTRY_POINT Driver Entry Point Access
 *
 * ___MANBRIEF___ driver entry point access functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the driver entry point access functions of CUDA
 * runtime application programming interface.
 *
 * @{
 */

/**
 * \brief Returns the requested driver API function pointer
 *
 * \deprecated This function is deprecated as of CUDA 13.0
 *
 *
 * Returns in \p **funcPtr the address of the CUDA driver function for the requested flags.
 *
 * For a requested driver symbol, if the CUDA version in which the driver symbol was
 * introduced is less than or equal to the CUDA runtime version, the API will return
 * the function pointer to the corresponding versioned driver function.
 *
 * The pointer returned by the API should be cast to a function pointer matching the
 * requested driver function's definition in the API header file. The function pointer
 * typedef can be picked up from the corresponding typedefs header file. For example,
 * cudaTypedefs.h consists of function pointer typedefs for driver APIs defined in cuda.h.
 *
 * The API will return ::cudaSuccess and set the returned \p funcPtr if the
 * requested driver function is valid and supported on the platform.
 *
 * The API will return ::cudaSuccess and set the returned \p funcPtr to NULL if the
 * requested driver function is not supported on the platform, no ABI
 * compatible driver function exists for the CUDA runtime version or if the
 * driver symbol is invalid.
 *
 * It will also set the optional \p driverStatus to one of the values in 
 * ::cudaDriverEntryPointQueryResult with the following meanings:
 * - ::cudaDriverEntryPointSuccess - The requested symbol was succesfully found based
 *   on input arguments and \p pfn is valid
 * - ::cudaDriverEntryPointSymbolNotFound - The requested symbol was not found
 * - ::cudaDriverEntryPointVersionNotSufficent - The requested symbol was found but is
 *   not supported by the current runtime version (CUDART_VERSION)
 *
 * The requested flags can be:
 * - ::cudaEnableDefault: This is the default mode. This is equivalent to
 *   ::cudaEnablePerThreadDefaultStream if the code is compiled with
 *   --default-stream per-thread compilation flag or the macro CUDA_API_PER_THREAD_DEFAULT_STREAM
 *   is defined; ::cudaEnableLegacyStream otherwise.
 * - ::cudaEnableLegacyStream: This will enable the search for all driver symbols
 *   that match the requested driver symbol name except the corresponding per-thread versions.
 * - ::cudaEnablePerThreadDefaultStream: This will enable the search for all
 *   driver symbols that match the requested driver symbol name including the per-thread
 *   versions. If a per-thread version is not found, the API will return the legacy version
 *   of the driver function.
 *
 * \param symbol - The base name of the driver API function to look for. As an example,
 *                 for the driver API ::cuMemAlloc_v2, \p symbol would be cuMemAlloc.
 *                 Note that the API will use the CUDA runtime version to return the
 *                 address to the most recent ABI compatible driver symbol, ::cuMemAlloc
 *                 or ::cuMemAlloc_v2.
 * \param funcPtr - Location to return the function pointer to the requested driver function
 * \param flags -  Flags to specify search options.
 * \param driverStatus - Optional location to store the status of finding the symbol from
 *                       the driver. See ::cudaDriverEntryPointQueryResult for 
 *                       possible values.
 *
 * \note This API is deprecated and ::cudaGetDriverEntryPointByVersion (with a hardcoded 
 *       ::cudaVersion) should be used instead.
 *
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \note_version_mixing
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuGetProcAddress
 */
#if defined(__cplusplus)
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPoint(const char *symbol, void **funcPtr, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus = NULL);
#else
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPoint(const char *symbol, void **funcPtr, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus);
#endif

/**
 * \brief Returns the requested driver API function pointer by CUDA version
 *
 * Returns in \p **funcPtr the address of the CUDA driver function for the requested flags and CUDA driver version.
 *
 * The CUDA version is specified as (1000 * major + 10 * minor), so CUDA 11.2
 * should be specified as 11020. For a requested driver symbol, if the specified
 * CUDA version is greater than or equal to the CUDA version in which the driver symbol
 * was introduced, this API will return the function pointer to the corresponding
 * versioned function. If the specified CUDA version is greater than the driver
 * version, the API will return ::cudaErrorInvalidValue.
 *
 * The pointer returned by the API should be cast to a function pointer matching the
 * requested driver function's definition in the API header file. The function pointer
 * typedef can be picked up from the corresponding typedefs header file. For example,
 * cudaTypedefs.h consists of function pointer typedefs for driver APIs defined in cuda.h.
 *
 * For the case where the CUDA version requested is greater than the CUDA Toolkit 
 * installed, there may not be an appropriate function pointer typedef in the
 * corresponding header file and may need a custom typedef to match the driver
 * function signature returned. This can be done by getting the typedefs from a later
 * toolkit or creating appropriately matching custom function typedefs.
 *
 * The API will return ::cudaSuccess and set the returned \p funcPtr if the
 * requested driver function is valid and supported on the platform.
 *
 * The API will return ::cudaSuccess and set the returned \p funcPtr to NULL if the
 * requested driver function is not supported on the platform, no ABI
 * compatible driver function exists for the requested version or if the
 * driver symbol is invalid.
 *
 * It will also set the optional \p driverStatus to one of the values in 
 * ::cudaDriverEntryPointQueryResult with the following meanings:
 * - ::cudaDriverEntryPointSuccess - The requested symbol was succesfully found based
 *   on input arguments and \p pfn is valid
 * - ::cudaDriverEntryPointSymbolNotFound - The requested symbol was not found
 * - ::cudaDriverEntryPointVersionNotSufficent - The requested symbol was found but is
 *   not supported by the specified version \p cudaVersion
 *
 * The requested flags can be:
 * - ::cudaEnableDefault: This is the default mode. This is equivalent to
 *   ::cudaEnablePerThreadDefaultStream if the code is compiled with
 *   --default-stream per-thread compilation flag or the macro CUDA_API_PER_THREAD_DEFAULT_STREAM
 *   is defined; ::cudaEnableLegacyStream otherwise.
 * - ::cudaEnableLegacyStream: This will enable the search for all driver symbols
 *   that match the requested driver symbol name except the corresponding per-thread versions.
 * - ::cudaEnablePerThreadDefaultStream: This will enable the search for all
 *   driver symbols that match the requested driver symbol name including the per-thread
 *   versions. If a per-thread version is not found, the API will return the legacy version
 *   of the driver function.
 *
 * \param symbol - The base name of the driver API function to look for. As an example,
 *                 for the driver API ::cuMemAlloc_v2, \p symbol would be cuMemAlloc.
 * \param funcPtr - Location to return the function pointer to the requested driver function
 * \param cudaVersion - The CUDA version to look for the requested driver symbol 
 * \param flags -  Flags to specify search options.
 * \param driverStatus - Optional location to store the status of finding the symbol from
 *                       the driver. See ::cudaDriverEntryPointQueryResult for 
 *                       possible values.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported
 * \note_version_mixing
 * \note_init_rt
 * \note_callback
 *
 * \sa
 * ::cuGetProcAddress
 */
#if defined(__cplusplus)
extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPointByVersion(const char *symbol, void **funcPtr, unsigned int cudaVersion, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus = NULL);
#else
extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPointByVersion(const char *symbol, void **funcPtr, unsigned int cudaVersion, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus);
#endif

/** @} */ /* END CUDART_DRIVER_ENTRY_POINT */

/**
 * \defgroup CUDART_LIBRARY Library Management
 *
 * ___MANBRIEF___ library management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the library management functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 */

/**
 * \brief Load a library with specified code and options
 *
 * Takes a pointer \p code and loads the corresponding library \p library based on
 * the application defined library loading mode:
 * - If module loading is set to EAGER, via the environment variables described in "Module loading",
 *   \p library is loaded eagerly into all contexts at the time of the call and future contexts
 *   at the time of creation until the library is unloaded with ::cudaLibraryUnload().
 * - If the environment variables are set to LAZY, \p library
 *   is not immediately loaded onto all existent contexts and will only be
 *   loaded when a function is needed for that context, such as a kernel launch.
 *
 * These environment variables are described in the CUDA programming guide under the 
 * "CUDA environment variables" section.
 *
 * The \p code may be a \e cubin or \e fatbin as output by \b nvcc,
 * or a NULL-terminated \e PTX, either as output by \b nvcc
 * or hand-written, or \e Tile IR data.
 * A fatbin should also contain relocatable code when doing separate compilation.
 * Please also see the documentation for nvrtc (https://docs.nvidia.com/cuda/nvrtc/index.html), 
 * nvjitlink (https://docs.nvidia.com/cuda/nvjitlink/index.html), and nvfatbin
 * (https://docs.nvidia.com/cuda/nvfatbin/index.html) for more information on generating
 * loadable code at runtime.
 *
 * Options are passed as an array via \p jitOptions and any corresponding parameters are passed in
 * \p jitOptionsValues. The number of total JIT options is supplied via \p numJitOptions.
 * Any outputs will be returned via \p jitOptionsValues.
 *
 * Library load options are passed as an array via \p libraryOptions and any corresponding parameters are passed in
 * \p libraryOptionValues. The number of total library load options is supplied via \p numLibraryOptions.
 *
 * \param library             - Returned library
 * \param code                - Code to load
 * \param jitOptions          - Options for JIT
 * \param jitOptionsValues    - Option values for JIT
 * \param numJitOptions       - Number of options
 * \param libraryOptions      - Options for loading
 * \param libraryOptionValues - Option values for loading
 * \param numLibraryOptions   - Number of options for loading
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorInitializationError,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInvalidPtx,
 * ::cudaErrorUnsupportedPtxVersion,
 * ::cudaErrorNoKernelImageForDevice,
 * ::cudaErrorSharedObjectSymbolNotFound,
 * ::cudaErrorSharedObjectInitFailed,
 * ::cudaErrorJitCompilerNotFound
 *
 * \sa ::cudaLibraryLoadFromFile,
 * ::cudaLibraryUnload,
 * ::cuLibraryLoadData
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryLoadData(cudaLibrary_t *library, const void *code,
                                   enum cudaJitOption *jitOptions, void **jitOptionsValues, unsigned int numJitOptions,
                                   enum cudaLibraryOption *libraryOptions, void** libraryOptionValues, unsigned int numLibraryOptions);

/**
 * \brief Load a library with specified file and options
 *
 * Takes a pointer \p code and loads the corresponding library \p library based on
 * the application defined library loading mode:
 * - If module loading is set to EAGER, via the environment variables described in "Module loading",
 *   \p library is loaded eagerly into all contexts at the time of the call and future contexts
 *   at the time of creation until the library is unloaded with ::cudaLibraryUnload().
 * - If the environment variables are set to LAZY, \p library
 *   is not immediately loaded onto all existent contexts and will only be
 *   loaded when a function is needed for that context, such as a kernel launch.
 *
 * These environment variables are described in the CUDA programming guide under the 
 * "CUDA environment variables" section.
 *
 * The file should be a \e cubin file as output by \b nvcc, or a \e PTX file either
 * as output by \b nvcc or handwritten, or a \e fatbin file as output by \b nvcc
 * or hand-written, or \e Tile IR file.
 * A fatbin should also contain relocatable code when doing separate compilation.
 * Please also see the documentation for nvrtc (https://docs.nvidia.com/cuda/nvrtc/index.html), 
 * nvjitlink (https://docs.nvidia.com/cuda/nvjitlink/index.html), and nvfatbin
 * (https://docs.nvidia.com/cuda/nvfatbin/index.html) for more information on generating
 * loadable code at runtime.
 *
 * Options are passed as an array via \p jitOptions and any corresponding parameters are
 * passed in \p jitOptionsValues. The number of total options is supplied via \p numJitOptions.
 * Any outputs will be returned via \p jitOptionsValues.
 *
 * Library load options are passed as an array via \p libraryOptions and any corresponding parameters are passed in
 * \p libraryOptionValues. The number of total library load options is supplied via \p numLibraryOptions.
 *
 * \param library             - Returned library
 * \param fileName            - File to load from
 * \param jitOptions          - Options for JIT
 * \param jitOptionsValues    - Option values for JIT
 * \param numJitOptions       - Number of options
 * \param libraryOptions      - Options for loading
 * \param libraryOptionValues - Option values for loading
 * \param numLibraryOptions   - Number of options for loading
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorMemoryAllocation,
 * ::cudaErrorInitializationError,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInvalidPtx,
 * ::cudaErrorUnsupportedPtxVersion,
 * ::cudaErrorNoKernelImageForDevice,
 * ::cudaErrorSharedObjectSymbolNotFound,
 * ::cudaErrorSharedObjectInitFailed,
 * ::cudaErrorJitCompilerNotFound
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryUnload,
 * ::cuLibraryLoadFromFile
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryLoadFromFile(cudaLibrary_t *library, const char *fileName,
                                       enum cudaJitOption *jitOptions, void **jitOptionsValues, unsigned int numJitOptions,
                                       enum cudaLibraryOption *libraryOptions, void **libraryOptionValues, unsigned int numLibraryOptions);

/**
 * \brief Unloads a library
 *
 * Unloads the library specified with \p library
 *
 * \param library - Library to unload
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryLoadFromFile,
 * ::cuLibraryUnload
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryUnload(cudaLibrary_t library);

/**
 * \brief Returns a kernel handle
 *
 * Returns in \p pKernel the handle of the kernel with name \p name located in library \p library.
 * If kernel handle is not found, the call returns ::cudaErrorSymbolNotFound.
 *
 * \param pKernel - Returned kernel handle
 * \param library - Library to retrieve kernel from
 * \param name - Name of kernel to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorSymbolNotFound
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryLoadFromFile,
 * ::cudaLibraryUnload,
 * ::cuLibraryGetKernel
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryGetKernel(cudaKernel_t *pKernel, cudaLibrary_t library, const char *name);

/**
 * \brief Returns a global device pointer
 *
 * Returns in \p *dptr and \p *bytes the base pointer and size of the global with
 * name \p name for the requested library \p library and the current device.
 * If no global for the requested name \p name exists, the call returns ::cudaErrorSymbolNotFound.
 * One of the parameters \p dptr or \p bytes (not both) can be NULL in which
 * case it is ignored. The returned \p dptr cannot be passed to the Symbol APIs
 * such as ::cudaMemcpyToSymbol, ::cudaMemcpyFromSymbol, ::cudaGetSymbolAddress, or
 * ::cudaGetSymbolSize.
 *
 * \param dptr - Returned global device pointer for the requested library
 * \param bytes - Returned global size in bytes
 * \param library - Library to retrieve global from
 * \param name - Name of global to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorSymbolNotFound
 * ::cudaErrorDeviceUninitialized,
 * ::cudaErrorContextIsDestroyed
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryLoadFromFile,
 * ::cudaLibraryUnload,
 * ::cudaLibraryGetManaged,
 * ::cuLibraryGetGlobal
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryGetGlobal(void **dptr, size_t *bytes, cudaLibrary_t library, const char *name);

/**
 * \brief Returns a pointer to managed memory
 *
 * Returns in \p *dptr and \p *bytes the base pointer and size of the managed memory with
 * name \p name for the requested library \p library. If no managed memory with the
 * requested name \p name exists, the call returns ::cudaErrorSymbolNotFound. One of the parameters
 * \p dptr or \p bytes (not both) can be NULL in which case it is ignored.
 * Note that managed memory for library \p library is shared across devices and is registered
 * when the library is loaded. The returned \p dptr cannot be passed to the Symbol APIs
 * such as ::cudaMemcpyToSymbol, ::cudaMemcpyFromSymbol, ::cudaGetSymbolAddress, or
 * ::cudaGetSymbolSize.
 *
 * \param dptr - Returned pointer to the managed memory
 * \param bytes - Returned memory size in bytes
 * \param library - Library to retrieve managed memory from
 * \param name - Name of managed memory to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorSymbolNotFound
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryLoadFromFile,
 * ::cudaLibraryUnload,
 * ::cudaLibraryGetGlobal,
 * ::cuLibraryGetManaged
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryGetManaged(void **dptr, size_t *bytes, cudaLibrary_t library, const char *name);

/**
 * \brief Returns a pointer to a unified function
 *
 * Returns in \p *fptr the function pointer to a unified function denoted by \p symbol.
 * If no unified function with name \p symbol exists, the call returns ::cudaErrorSymbolNotFound.
 * If there is no device with attribute ::cudaDeviceProp::unifiedFunctionPointers present in the system,
 * the call may return ::cudaErrorSymbolNotFound.
 *
 * \param fptr - Returned pointer to a unified function
 * \param library - Library to retrieve function pointer memory from
 * \param symbol - Name of function pointer to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle,
 * ::cudaErrorSymbolNotFound
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryLoadFromFile,
 * ::cudaLibraryUnload,
 * ::cuLibraryGetUnifiedFunction
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryGetUnifiedFunction(void **fptr, cudaLibrary_t library, const char *symbol);

/**
 * \brief Returns the number of kernels within a library
 *
 * Returns in \p count the number of kernels in \p lib.
 *
 * \param count - Number of kernels found within the library
 * \param lib - Library to query
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 *
 * \sa ::cudaLibraryEnumerateKernels,
 * ::cudaLibraryLoadFromFile,
 * ::cudaLibraryLoadData,
 * ::cuLibraryGetKernelCount
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryGetKernelCount(unsigned int *count, cudaLibrary_t lib);

/**
 * \brief Retrieve the kernel handles within a library.
 *
 * Returns in \p kernels a maximum number of \p numKernels kernel handles within \p lib.
 * The returned kernel handle becomes invalid when the library is unloaded.
 *
 * \param kernels - Buffer where the kernel handles are returned to
 * \param numKernels - Maximum number of kernel handles may be returned to the buffer
 * \param lib - Library to query from
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidResourceHandle
 *
 * \sa ::cudaLibraryGetKernelCount,
 * ::cuLibraryEnumerateKernels
 */
extern __host__ cudaError_t CUDARTAPI cudaLibraryEnumerateKernels(cudaKernel_t *kernels, unsigned int numKernels, cudaLibrary_t lib);

/**
 * \brief Sets information about a kernel
 *
 * This call sets the value of a specified attribute \p attr on the kernel \p kernel
 * for the requested device \p device to an integer value specified by \p value.
 * This function returns ::cudaSuccess if the new value of the attribute could be
 * successfully set. If the set fails, this call will return an error.
 * Not all attributes can have values set. Attempting to set a value on a read-only
 * attribute will result in an error (::cudaErrorInvalidValue)
 *
 * Note that attributes set using ::cudaFuncSetAttribute() will override the attribute
 * set by this API irrespective of whether the call to ::cudaFuncSetAttribute() is made
 * before or after this API call. Because of this and the stricter locking requirements
 * mentioned below it is suggested that this call be used during the initialization path
 * and not on each thread accessing \p kernel such as on kernel launches or on the
 * critical path.
 *
 * Valid values for \p attr are:
 * - ::cudaFuncAttributeMaxDynamicSharedMemorySize - The requested maximum size in bytes of dynamically-allocated shared memory. The sum of this value and the function attribute ::sharedSizeBytes
 *   cannot exceed the device attribute ::cudaDevAttrMaxSharedMemoryPerBlockOptin. The maximal size of requestable dynamic shared memory may differ by GPU architecture.
 * - ::cudaFuncAttributePreferredSharedMemoryCarveout - On devices where the L1 cache and shared memory use the same hardware resources, 
 *   this sets the shared memory carveout preference, in percent of the total shared memory. See ::cudaDevAttrMaxSharedMemoryPerMultiprocessor.
 *   This is only a hint, and the driver can choose a different ratio if required to execute the function.
 * - ::cudaFuncAttributeRequiredClusterWidth: The required cluster width in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return cudaErrorNotPermitted.
 * - ::cudaFuncAttributeRequiredClusterHeight: The required cluster height in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return cudaErrorNotPermitted.
 * - ::cudaFuncAttributeRequiredClusterDepth: The required cluster depth in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return cudaErrorNotPermitted.
 * - ::cudaFuncAttributeNonPortableClusterSizeAllowed: Indicates whether the
 *   function can be launched with non-portable cluster size. 1 is allowed, 0 is
 *   disallowed.
 * - ::cudaFuncAttributeClusterSchedulingPolicyPreference: The block
 *   scheduling policy of a function. The value type is cudaClusterSchedulingPolicy.
 *
 * \note The API has stricter locking requirements in comparison to its legacy counterpart
 * ::cudaFuncSetAttribute() due to device-wide semantics. If multiple threads are trying to
 * set the same attribute on the same device simultaneously, the attribute setting will depend
 * on the interleavings chosen by the OS scheduler and memory consistency.
 *
 * \param kernel  - Kernel to set attribute of
 * \param attr - Attribute requested
 * \param value - Value to set
 * \param device - Device to set attribute of
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidDeviceFunction,
 * ::cudaErrorInvalidValue
 *
 * \sa ::cudaLibraryLoadData,
 * ::cudaLibraryLoadFromFile,
 * ::cudaLibraryUnload,
 * ::cudaLibraryGetKernel,
 * ::cudaLaunchKernel,
 * ::cudaFuncSetAttribute,
 * ::cuKernelSetAttribute
 */
extern __host__ cudaError_t CUDARTAPI cudaKernelSetAttributeForDevice(cudaKernel_t kernel, enum cudaFuncAttribute attr, int value, int device);

/** @} */ /* END CUDART_LIBRARY */

/**
 * \defgroup CUDART_EXECUTION_CONTEXT Execution Context Management
 *
 * ___MANBRIEF___ execution context management functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the execution context management functions of the CUDA runtime
 * application programming interface.
 *
 * @{
 *
 * \section CUDART_EXECUTION_CONTEXT_overview Overview
 *
 * A CUDA execution context ::cudaExecutionContext_t serves as an abstraction for the contexts exposed by the CUDA Runtime,
 * specifically green contexts and the primary context, and provides a unified programming model and API interface for contexts
 * in the Runtime.
 *
 * There are two primary ways today to obtain an execution context:
 * - ::cudaDeviceGetExecutionCtx: Returns the execution context that corresponds to the primary context of the specified device.
 * - ::cudaGreenCtxCreate: Creates a green context with the specified resources and returns an execution context.
 *
 * Once you have an execution context at hand, you can perform context-level operations via the CUDA Runtime APIs. This includes:
 * - Submitting work via streams created with ::cudaExecutionCtxStreamCreate.
 * - Querying context via ::cudaExecutionCtxGetDevResource, ::cudaExecutionCtxGetDevice, etc.
 * - Synchronizing and tracking context-level operations via ::cudaExecutionCtxSynchronize, ::cudaExecutionCtxRecordEvent, ::cudaExecutionCtxWaitEvent.
 * - Performing context-level graph node operations via ::cudaGraphAddNode by specifying the context in \p nodeParams. Note that individual node creation APIs,
 *   such as ::cudaGraphAddKernelNode, do not support specifying an execution context.
 *
 * Note: The above APIs take in an explicit cudaExecutionContext_t handle and ignores the context that is current to the calling thread.
 * This enables explicit context-based programming without relying on thread-local state. If no context is specified,
 * the APIs return ::cudaErrorInvalidValue.
 *
 * Note: Developers should treat ::cudaExecutionContext_t as an opaque handle and avoid assumptions
 * about its underlying representation. The CUDA Runtime does not provide a way to convert this
 * handle into driver-level contexts, such as ::CUcontext or ::CUgreenCtx.
 *
 * \section CUDART_EXECUTION_CONTEXT_lifetimeOfCUDAResources Lifetime of CUDA Resources
 * The lifetime of CUDA resources (memory, streams, events, modules, etc) is not tied to the lifetime
 * of the execution context. Their lifetime is tied to the device against which they were created.
 * As such, usage of ::cudaDeviceReset() should be avoided to persist the lifetime of these resources.
 *
 * \section CUDART_EXECUTION_CONTEXT APIs Operating on Current Context
 * The CUDA runtime does not provide a way to set an execution context as current. Since, the majority of
 * the runtime APIs operate on the current context, we document below how the developer can work with
 * these APIs.
 *
 * \subsection CUDART_EXECUTION_CONTEXT_currentContext_deviceResources APIs Operating on Device Resources
 * To work with these APIs (for example, ::cudaMalloc, ::cudaEventCreate, etc), developers are expected
 * to call ::cudaSetDevice() prior to invoking them. Doing so does not impact functional correctness as
 * these APIs operate on resources that are device-wide. If users have a context handle at hand, they
 * can get the device handle from the context handle using ::cudaExecutionCtxGetDevice().
 *
 * \subsection CUDART_EXECUTION_CONTEXT_currentContext_contextResources APIs Operating on Context Resources
 * These APIs (for example, ::cudaLaunchKernel, ::cudaMemcpyAsync, ::cudaMemsetAsync, etc) take in
 * a stream and resources are inferred from the context bound to the stream at creation. See ::cudaExecutionCtxStreamCreate
 * for more details. Developers are expected to use the stream-based APIs for context awareness and
 * always pass an explicit stream handle to ensure context-awareness, and avoid reliance on the default NULL stream,
 * which implicitly binds to the current context.
 *
 * \section CUDART_CONTEXT_greencontexts Green Contexts
 *
 * Green contexts are a lightweight alternative to traditional contexts, that can be used to select
 * a subset of device resources. This allows the developer to, for example, select SMs from distinct spatial
 * partitions of the GPU and target them via CUDA stream operations, kernel launches, etc.
 *
 * Here are the broad initial steps to follow to get started:
 * - (1) Start with an initial set of resources. For SM resources, they can be fetched via ::cudaDeviceGetDevResource.
 *  In case of workqueues, a new configuration can be used or an existing one queried via the ::cudaDeviceGetDevResource API.
 * - (2) Modify these resources by either partitioning them (in case of SMs) or changing the configuration (in case of workqueues).
 *  To partition SMs, we recommend ::cudaDevSmResourceSplit. Changing the workqueue configuration can be done directly in place.
 * - (3) Finalize the specification of resources by creating a descriptor via ::cudaDevResourceGenerateDesc.
 * - (4) Create a green context via ::cudaGreenCtxCreate. This provisions the resource, such as workqueues
 *  (until this step it was only a configuration specification).
 * - (5) Create a stream via ::cudaExecutionCtxStreamCreate, and use it throughout your application.
 *
 * <b>SMs</b>
 *
 * There are two possible partition operations - with ::cudaDevSmResourceSplitByCount the partitions created have to follow default
 * SM count granularity requirements, so it will often be rounded up and aligned to a default value. On the other hand,
 * ::cudaDevSmResourceSplit is explicit and allows for creation of non-equal groups. It will not round up automatically - instead
 * it is the developer’s responsibility to query and set the correct values.
 * These requirements can be queried with ::cudaDeviceGetDevResource to determine the alignment granularity (sm.smCoscheduledAlignment).
 * A general guideline on the default values for each compute architecture:
 * - On Compute Architecture 7.X, 8.X, and all Tegra SoC:
 *   - The smCount must be a multiple of 2.
 *   - The alignment (and default value of coscheduledSmCount) is 2.
 * - On Compute Architecture 9.0+:
 *   - The smCount must be a multiple of 8, or coscheduledSmCount if provided.
 *   - The alignment (and default value of coscheduledSmCount) is 8.
 * While the maximum value for coscheduled SM count is 32 on all Compute Architecture 9.0+, it's recommended to follow cluster size requirements.
 * The portable cluster size and the max cluster size should be used in order to benefit from this co-scheduling.
 *
 * <b>Workqueues</b>
 *
 * For \p cudaDevResourceTypeWorkqueueConfig, the resource specifies the expected maximum number of concurrent stream-ordered
 * workloads via the \p wqConcurrencyLimit field. The \p sharingScope field determines how workqueue resources are shared:
 * - \p cudaDevWorkqueueConfigScopeDeviceCtx: Use all shared workqueue resources across all contexts (default driver behavior).
 * - \p cudaDevWorkqueueConfigScopeGreenCtxBalanced: When possible, use non-overlapping workqueue resources with other balanced green contexts.
 *
 * The maximum concurrency limit depends on ::CUDA_DEVICE_MAX_CONNECTIONS and can be queried from the device via ::cudaDeviceGetDevResource.
 * Configurations may exceed this concurrency limit, but the driver will not guarantee that work submission remains non-overlapping.
 *
 * For \p cudaDevResourceTypeWorkqueue, the resource represents a pre-existing workqueue that can be retrieved from existing
 * execution contexts. This allows reusing workqueue resources across different execution contexts.
 *
 * <b>On Concurrency</b>
 *
 * Even if the green contexts have disjoint SM partitions, it is not guaranteed that the kernels launched in them will run concurrently
 * or have forward progress guarantees. This is due to other resources that could cause a dependency. Using a combination of disjoint SMs
 * and \p cudaDevWorkqueueConfigScopeGreenCtxBalanced workqueue configurations can provide the best chance of avoiding interference.
 * More resources will be added in the future to provide stronger guarantees.
 *
 * Additionally, there are two known scenarios, where its possible for the workload to run on more SMs than was provisioned (but never less).
 *
 * - On Volta+ MPS: When \p CUDA_MPS_ACTIVE_THREAD_PERCENTAGE is used,
 * the set of SMs that are used for running kernels can be scaled up to the value of SMs used for the MPS client.
 * - On Compute Architecture 9.x: When a module with dynamic parallelism (CDP) is loaded, all future
 * kernels running under green contexts may use and share an additional set of 2 SMs.
 */

/**
 * \brief Get device resources
 *
 * Get the \p type resources available to the \p device.
 * This may often be the starting point for further partitioning or configuring
 * of resources.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param device - Device to get resource for
 * \param resource - Output pointer to a cudaDevResource structure
 * \param type - Type of resource to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorInvalidResourceType,
 * ::cudaErrorNotSupported,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \note_callback
 *
 * \sa
 * ::cuDeviceGetDevResource,
 * ::cudaExecutionCtxGetDevResource,
 * ::cudaDevSmResourceSplit,
 * ::cudaDevResourceGenerateDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetDevResource(int device, cudaDevResource *resource, enum cudaDevResourceType type);

/**
 * \brief Splits \p cudaDevResourceTypeSm resources.
 *
 * Splits \p cudaDevResourceTypeSm resources into \p nbGroups, adhering to the
 * minimum SM count specified in \p minCount and the usage flags in \p flags.
 * If \p result is NULL, the API simulates a split and provides the amount of groups that
 * would be created in \p nbGroups. Otherwise, \p nbGroups must point to the amount of elements
 * in \p result and on return, the API will overwrite \p nbGroups with the amount actually created.
 * The groups are written to the array in \p result.
 * \p nbGroups can be less than the total amount if a smaller number of groups is needed.
 *
 * This API is used to spatially partition the input resource. The input resource needs to come
 * from one of ::cudaDeviceGetDevResource, or ::cudaExecutionCtxGetDevResource.
 * A limitation of the API is that the output results cannot be split again without
 * first creating a descriptor and a green context with that descriptor.
 *
 * When creating the groups, the API will take into account the performance and functional
 * characteristics of the input resource, and guarantee a split that will create a disjoint
 * set of symmetrical partitions. This may lead to fewer groups created than purely dividing
 * the total SM count by the \p minCount due to cluster requirements or alignment and granularity
 * requirements for the minCount.
 * These requirements can be queried with ::cudaDeviceGetDevResource, or ::cudaExecutionCtxGetDevResource
 * for ::cudaDevResourceTypeSm, using the \p minSmPartitionSize and \p smCoscheduledAlignment fields
 * to determine minimum partition size and alignment granularity, respectively.
 *
 * The \p remainder set does not have the same functional or performance guarantees as the groups
 * in \p result. Its use should be carefully planned and future partitions of the \p remainder set
 * are discouraged.
 *
 * The following flags are supported:
 * - \p cudaDevSmResourceSplitIgnoreSmCoscheduling : Lower the minimum SM count and alignment, and
 *   treat each SM independent of its hierarchy. This allows more fine grained partitions but at the
 *   cost of advanced features (such as large clusters on compute capability 9.0+).
 * - \p cudaDevSmResourceSplitMaxPotentialClusterSize : Compute Capability 9.0+ only. Attempt to
 *   create groups that may allow for maximally sized thread clusters. This can be queried post
 *   green context creation using ::cudaOccupancyMaxPotentialClusterSize.
 *
 * A successful API call must either have:
 * - A valid array of \p result pointers of size passed in \p nbGroups, with \p input of type
 *   \p cudaDevResourceTypeSm. Value of \p minCount must be between 0 and the SM count specified
 *   in \p input. \p remaining may be NULL.
 * - NULL passed in for \p result, with a valid integer pointer in \p nbGroups and \p input of
 *   type \p cudaDevResourceTypeSm. Value of \p minCount must be between 0 and the SM count
 *   specified in \p input. \p remaining may be NULL. This queries the number of groups that
 *   would be created by the API.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param result - Output array of \p cudaDevResource resources. Can be NULL to query the
 * number of groups.
 * \param nbGroups - This is a pointer, specifying the number of groups that would be or
 * should be created as described below.
 * \param input - Input SM resource to be split. Must be a valid \p cudaDevSmResource resource.
 * \param remaining - If the input resource cannot be cleanly split among \p nbGroups,
 * the remaining is placed in here. Can be ommitted (NULL) if the user does not need the remaining set.
 * \param flags - Flags specifying how these partitions are used or which constraints to abide by
 * when splitting the input. Zero is valid for default behavior.
 * \param minCount - Minimum number of SMs required
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorInvalidResourceType,
 * ::cudaErrorInvalidResourceConfiguration,
 * ::cudaErrorNotSupported,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \note_callback
 *
 * \sa
 * ::cuDevSmResourceSplitByCount,
 * ::cudaDeviceGetDevResource,
 * ::cudaExecutionCtxGetDevResource,
 * ::cudaDevResourceGenerateDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaDevSmResourceSplitByCount(
    cudaDevResource *result, unsigned int *nbGroups, const cudaDevResource *input, cudaDevResource *remaining, unsigned int flags, unsigned int minCount);

/**
 * \brief Splits a \p cudaDevResourceTypeSm resource into structured groups.
 *
 * This API will split a resource of ::cudaDevResourceTypeSm into \p nbGroups structured device resource groups (the \p result array),
 * as well as an optional \p remainder, according to a set of requirements specified in the \p groupParams array. The term “structured”
 * is a trait that specifies the \p result has SMs that are co-scheduled together. This co-scheduling can be specified via the \p coscheduledSmCount
 * field of the \p groupParams structure, while the \p smCount will specify how many SMs are required in total for that result.
 * The remainder is always “unstructured”, it does not have any set guarantees with respect to co-scheduling and those properties will need to
 * either be queried via the occupancy set of APIs or further split into structured groups by this API.
 *
 * The API has a discovery mode for use cases where it is difficult to know ahead of time what the SM count should be.
 * Discovery happens when the \p smCount field of a given \p groupParams array entry is set to 0 - the smCount will be filled in by the API
 * with the derived SM count according to the provided \p groupParams fields and constraints. Discovery can be used with both a valid result
 * array and with a NULL \p result pointer value. The latter is useful in situations where the smCount will end up being zero, which is an invalid
 * value to create a result entry with, but allowed for discovery purposes when the \p result is NULL.
 *
 * The \p groupParams array is evaluated from index 0 to \p nbGroups - 1. For each index in the \p groupParams array,
 * the API will evaluate which SMs may be a good fit based on constraints and assign those SMs to \p result.
 * This evaluation order is important to consider when using discovery mode, as it helps discover the remaining SMs.
 *
 * For a valid call:
 * - \p result should point to a \p cudaDevResource array of size \p nbGroups, or alternatively, may be NULL, if the developer wishes for only the groupParams entries to be updated
 *
 * - \p input should be a valid ::cudaDevResourceTypeSm resource that originates from querying the execution context, or device.
 *
 * - The \p remainder group may be NULL.
 *
 * - There are no API \p flags at this time, so the value passed in should be 0.
 *
 * - A ::cudaDevSmResourceGroupParams array of size \p nbGroups. Each entry must be zero-initialized.
 *     - \p smCount: must be either 0 or in the range of [2,inputSmCount] where inputSmCount is the amount of SMs the \p input resource has.
 *     \p smCount must be a multiple of 2, as well as a multiple of \p coscheduledSmCount. When assigning SMs to a group (and if results are
 *     expected by having the \p result parameter set), \p smCount cannot end up with 0 or a value less than \p coscheduledSmCount
 *     otherwise ::cudaErrorInvalidResourceConfiguration will be returned.
 *     - \p coscheduledSmCount: allows grouping SMs together in order to be able to launch clusters on Compute Architecture 9.0+.
 *     The default value may be queried from the device’s ::cudaDevResourceTypeSm resource (8 on Compute Architecture 9.0+ and 2 otherwise).
 *     The maximum is 32 on Compute Architecture 9.0+ and 2 otherwise.
 *     - \p preferredCoscheduledSmCount: Attempts to merge \p coscheduledSmCount groups into larger groups,
 *     in order to make use of \p preferredClusterDimensions on Compute Architecture 10.0+. The default value is set to \p coscheduledSmCount.
 *     - \p flags:
 *         - \p cudaDevSmResourceGroupBackfill: lets \p smCount be a non-multiple of \p coscheduledSmCount, filling the difference between SM count
 *         and already assigned co-scheduled groupings with other SMs. This lets any resulting group behave similar to the \p remainder group for example.
 *
 * <b>Example params and their effect:</b>
 *
 * A groupParams array element is defined in the following order:
 * \code
 * { .smCount, .coscheduledSmCount, .preferredCoscheduledSmCount, .flags, \/\* .reserved \*\/ }
 * \endcode
 *
 * \code
// Example 1
// Will discover how many SMs there are, that are co-scheduled in groups of smCoscheduledAlignment.
// The rest is placed in the optional remainder.
cudaDevSmResourceGroupParams params { 0, 0, 0, 0 };
 * \endcode
 * \code
// Example 2
// Assuming the device has 10+ SMs, the result will have 10 SMs that are co-scheduled in groups of 2 SMs.
// The rest is placed in the optional remainder.
cudaDevSmResourceGroupParams params { 10, 2, 0, 0};
// Setting the coscheduledSmCount to 2 guarantees that we can always have a valid result
// as long as the SM count is less than or equal to the input resource SM count.
 * \endcode
 * \code
// Example 3
// A single piece is split-off, but instead of assigning the rest to the remainder, a second group contains everything else
// This assumes the device has 10+ SMs (8 of which are coscheduled in groups of 4),
// otherwise the second group could end up with 0 SMs, which is not allowed.
cudaDevSmResourceGroupParams params { {8, 4, 0, 0}, {0, 2, 0, cudaDevSmResourceGroupBackfill } }
 * \endcode
 *
 * The difference between a catch-all param group as the last entry and the remainder is in two aspects:
 * - The remainder may be NULL / _TYPE_INVALID (if there are no SMs remaining), while a result group must always be valid.
 * - The remainder does not have a structure, while the result group will always need to adhere to a structure
 * of coscheduledSmCount (even if its just 2), and therefore must always have enough coscheduled SMs to cover
 * that requirement (even with the \p cudaDevSmResourceGroupBackfill flag enabled).
 *
 * Splitting an input into N groups, can be accomplished by repeatedly splitting off 1 group and re-splitting
 * the remainder (a bisect operation). However, it's recommended to accomplish this with a single call wherever possible.
 *
 * \param result - Output array of \p cudaDevResource resources. Can be NULL, alongside an smCount of 0, for discovery purpose.
 * \param nbGroups - Specifies the number of groups in \p result and \p groupParams
 * \param input - Input SM resource to be split. Must be a valid \p cudaDevResourceTypeSm resource.
 * \param remainder - If splitting the input resource leaves any SMs, the remainder is placed in here.
 * \param flags - Flags specifying how the API should behave. The value should be 0 for now.
 * \param groupParams - Description of how the SMs should be split and assigned to the corresponding result entry.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorInvalidResourceType,
 * ::cudaErrorInvalidResourceConfiguration,
 * ::cudaErrorNotSupported,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \note_callback
 *
 * \sa
 * ::cuDevSmResourceSplit,
 * ::cudaDeviceGetDevResource,
 * ::cudaExecutionCtxGetDevResource,
 * ::cudaDevResourceGenerateDesc
 */
extern __host__ cudaError_t CUDARTAPI cudaDevSmResourceSplit(
    cudaDevResource* result, unsigned int nbGroups, const cudaDevResource* input, cudaDevResource* remainder, unsigned int flags, cudaDevSmResourceGroupParams* groupParams);

/**
 * \brief Generate a resource descriptor
 *
 * Generates a single resource descriptor with the set of resources specified in \p resources.
 * The generated resource descriptor is necessary for the creation of green contexts via the
 * ::cudaGreenCtxCreate API. Resources of the same type can be passed in, provided they meet
 * the requirements as noted below.
 *
 * A successful API call must have:
 * - A valid output pointer for the \p phDesc descriptor as well as a valid array of \p resources pointers,
 * with the array size passed in \p nbResources.
 * If multiple resources are provided in \p resources, the device they came from must be the same,
 * otherwise ::cudaErrorInvalidResourceConfiguration is returned.
 * If multiple resources are provided in \p resources and they are of type ::cudaDevResourceTypeSm,
 * they must be outputs (whether \p result or \p remaining) from the same split API instance and have
 * the same smCoscheduledAlignment values, otherwise ::cudaErrorInvalidResourceConfiguration is returned.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param phDesc - Output descriptor
 * \param resources - Array of resources to be included in the descriptor
 * \param nbResources - Number of resources passed in \p resources
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorInvalidResourceType,
 * ::cudaErrorInvalidResourceConfiguration,
 * ::cudaErrorNotSupported,
 * ::cudaErrorOutOfMemory,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \note_callback
 *
 * \sa
 * ::cuDevResourceGenerateDesc,
 * ::cudaDeviceGetDevResource,
 * ::cudaExecutionCtxGetDevResource,
 * ::cudaDevSmResourceSplit,
 * ::cudaGreenCtxCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaDevResourceGenerateDesc(cudaDevResourceDesc_t *phDesc, cudaDevResource *resources, unsigned int nbResources);

/**
 * \brief Creates a green context with a specified set of resources.
 *
 * This API creates a green context with the resources specified in the descriptor \p desc and
 * returns it in the handle represented by \p phCtx.
 *
 * This API retains the device’s primary context for the lifetime of the green context.
 * The primary context will be released when the green context is destroyed. To avoid the
 * overhead of repeated initialization and teardown, it is recommended to explicitly
 * initialize the device's primary context ahead of time using ::cudaInitDevice. This
 * ensures that the primary context remains initialized throughout the program’s lifetime,
 * minimizing overhead during green context creation and destruction.
 *
 * The API does not create a default stream for the green context. Developers are expected
 * to create streams explicitly using ::cudaExecutionCtxStreamCreate to submit work
 * to the green context.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param phCtx - Pointer for the output handle to the green context
 * \param desc - Descriptor generated via ::cudaDevResourceGenerateDesc which contains the set of resources to be used
 * \param device - Device on which to create the green context.
 * \param flags - Green context creation flags. Must be 0, currently reserved for future use.
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorNotSupported,
 * ::cudaErrorOutOfMemory,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \note_callback
 *
 * \sa
 * ::cudaDeviceGetDevResource,
 * ::cudaDevSmResourceSplit,
 * ::cudaDevResourceGenerateDesc,
 * ::cudaExecutionCtxGetDevResource,
 * ::cudaExecutionCtxDestroy,
 * ::cudaInitDevice,
 * ::cudaExecutionCtxStreamCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaGreenCtxCreate(cudaExecutionContext_t *phCtx, cudaDevResourceDesc_t desc, int device, unsigned int flags);

/**
 * \brief Destroy a execution context
 *
 * Destroys the specified execution context \p ctx. It is the responsibility of the caller
 * to ensure that no API call issues using \p ctx while ::cudaExecutionCtxDestroy() is executing or
 * subsequently.
 *
 * If \p ctx is a green context, any resources provisioned for it (that were initially available via the resource descriptor)
 * are released as well.
 *
 * The API does not destroy streams created via ::cudaExecutionCtxStreamCreate. Users are expected to
 * destroy these streams explicitly using ::cudaStreamDestroy to avoid resource leaks. Once the
 * execution context is destroyed, any subsequent API calls involving these streams will return
 * ::cudaErrorStreamDetached with the exception of the following APIs:
 * - ::cudaStreamDestroy. Note this is only supported on CUDA drivers 13.1 and above.
 *
 * Additionally, the API will invalidate all active captures on these streams.
 *
 * Passing in a \p ctx that was not explicitly created via CUDA Runtime APIs is not allowed and will
 * result in undefined behavior.
 *
 * \param ctx - Execution context to destroy (required parameter, see note below)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa
 * ::cudaGreenCtxCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxDestroy(cudaExecutionContext_t ctx);

/**
 * \brief Get context resources
 *
 * Get the \p type resources available to context represented by \p ctx.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param ctx - Execution context to get resource for (required parameter, see note below)
 * \param resource - Output pointer to a cudaDevResource structure
 * \param type - Type of resource to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotSupported,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa
 * ::cudaDeviceGetDevResource,
 * ::cudaDevSmResourceSplit,
 * ::cudaDevResourceGenerateDesc,
 * ::cudaGreenCtxCreate
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxGetDevResource(cudaExecutionContext_t ctx, cudaDevResource *resource, enum cudaDevResourceType type);

/**
 * \brief Returns the device handle for the execution context
 *
 * Returns in \p *device the handle of the specified execution context's device.
 * The execution context should not be NULL.
 *
 * \param device - Returned device handle for the specified execution context
 * \param ctx - Execution context for which to obtain the device (required parameter, see note below)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa ::cudaGreenCtxCreate,
 * ::cudaExecutionCtxDestroy,
 * ::cuCtxGetDevice
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxGetDevice(int *device, cudaExecutionContext_t ctx);

/**
 * \brief Returns the unique Id associated with the execution context supplied
 *
 * Returns in \p ctxId the unique Id which is associated with a given context.
 * The Id is unique for the life of the program for this instance of CUDA.
 * The execution context should not be NULL.
 *
 * \param ctx - Context for which to obtain the Id (required parameter, see note below)
 * \param ctxId - Pointer to store the Id of the context
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa ::cudaGreenCtxCreate,
 * ::cudaExecutionCtxDestroy,
 * ::cudaExecutionCtxGetDevice,
 * ::cuCtxGetId
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxGetId(cudaExecutionContext_t ctx, unsigned long long *ctxId);

/**
 * \brief Creates a stream and initializes it for the given execution context.
 *
 * The API creates a CUDA stream with the specified \p flags and \p priority,
 * initializing it with resources as defined at the time of creating the specified \p ctx.
 * Additionally, the API also enables work submitted to to the stream to be tracked under \p ctx.
 *
 * The supported values for \p flags are:
 * - ::cudaStreamDefault: Default stream creation flag. This would be ::cudaStreamNonBlocking for
 *   streams created on a green context.
 * - ::cudaStreamNonBlocking: Specifies that work running in the created stream may run concurrently
 *   with work in stream 0 (the NULL stream), and that the created stream should perform no implicit
 *   synchronization with stream 0
 *
 * Specifying \p priority affects the scheduling priority of work in the stream. Priorities provide a
 * hint to preferentially run work with higher priority when possible, but do not preempt
 * already-running work or provide any other functional guarantee on execution order.
 * \p priority follows a convention where lower numbers represent higher priorities.
 * '0' represents default priority. The range of meaningful numerical priorities can
 * be queried using ::cudaDeviceGetStreamPriorityRange. If the specified priority is
 * outside the numerical range returned by ::cudaDeviceGetStreamPriorityRange,
 * it will automatically be clamped to the lowest or the highest number in the range.
 *
 * \param phStream - Returned stream handle
 * \param ctx      - Execution context to initialize the stream with (required parameter, see note below)
 * \param flags    - Flags for stream creation
 * \param priority - Stream priority
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorOutOfMemory,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \note In the current implementation, only compute kernels launched in
 * priority streams are affected by the stream's priority. Stream priorities have
 * no effect on host-to-device and device-to-host memory operations.
 *
 * \sa ::cudaStreamDestroy,
 * ::cudaGreenCtxCreate,
 * ::cudaDeviceGetStreamPriorityRange,
 * ::cudaStreamGetFlags,
 * ::cudaStreamGetPriority,
 * ::cudaStreamGetDevice,
 * ::cudaStreamGetDevResource,
 * ::cudaLaunchKernel,
 * ::cudaEventRecord,
 * ::cudaStreamWaitEvent,
 * ::cudaStreamQuery,
 * ::cudaStreamSynchronize,
 * ::cudaStreamAddCallback
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxStreamCreate(cudaStream_t *phStream, cudaExecutionContext_t ctx, unsigned int flags, int priority);

/**
 * \brief Block for the specified execution context's tasks to complete
 *
 * Blocks until the specified execution context has completed all preceding requested tasks.
 * If the specified execution context is the device (primary) context obtained via ::cudaDeviceGetExecutionCtx,
 * green contexts that have been created on the device will also be synchronized.
 *
 * The API returns an error if one of the preceding tasks failed.
 *
 * \param ctx - Execution context to synchronize (required parameter, see note below)
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorDeviceUninitialized,
 * ::cudaErrorInvalidValue
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa
 * ::cudaGreenCtxCreate,
 * ::cudaExecutionCtxDestroy,
 * ::cudaDeviceSynchronize,
 * ::cuCtxSynchronize_v2
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxSynchronize(cudaExecutionContext_t ctx);

/**
 * \brief Get stream resources
 *
 * Get the \p type resources available to the \p hStream and store them in \p resource.
 *
 * Note: The API will return ::cudaErrorInvalidResourceType is \p type is
 * \p cudaDevResourceTypeWorkqueueConfig or \p cudaDevResourceTypeWorkqueue.
 *
 * \param hStream - Stream to get resource for
 * \param resource - Output pointer to a cudaDevResource structure
 * \param type - Type of resource to retrieve
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorDeviceUninitialized,
 * ::cudaErrorInvalidResourceType,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidHandle,
 * ::cudaErrorNotPermitted,
 * ::cudaErrorCallRequiresNewerDriver,
 * \notefnerr
 * \note_callback
 *
 * \sa
 * ::cudaGreenCtxCreate,
 * ::cudaExecutionCtxStreamCreate,
 * ::cudaStreamCreate,
 * ::cudaDevSmResourceSplit,
 * ::cudaDevResourceGenerateDesc,
 * ::cuStreamGetDevResource
 */
extern __host__ cudaError_t CUDARTAPI cudaStreamGetDevResource(cudaStream_t hStream, cudaDevResource *resource, enum cudaDevResourceType type);

/**
 * \brief Records an event for the specified execution context
 *
 * Captures in \p event all the activities of the execution context \p ctx
 * at the time of this call. \p event and \p ctx must be from the same
 * CUDA device, otherwise ::cudaErrorInvalidHandle will be returned.
 * Calls such as ::cudaEventQuery() or ::cudaExecutionCtxWaitEvent() will then examine
 * or wait for completion of the work that was captured.
 * Uses of \p ctx after this call do not modify \p event.
 * If the execution context passed to \p ctx is the device (primary) context obtained via
 * ::cudaDeviceGetExecutionCtx(), \p event will capture all the activities of the green
 * contexts created on the device as well.
 *
 * \note The API will return ::cudaErrorStreamCaptureUnsupported if the
 * specified execution context \p ctx has a stream in the capture mode. In such a case,
 * the call will invalidate all the conflicting captures.
 *
 * \param ctx - Execution context to record event for (required parameter, see note below)
 * \param event - Event to record
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidHandle,
 * ::cudaErrorStreamCaptureUnsupported
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa
 * ::cudaEventRecord,
 * ::cudaExecutionCtxWaitEvent,
 * ::cuCtxRecordEvent,
 * ::cuGreenCtxRecordEvent
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxRecordEvent(cudaExecutionContext_t ctx, cudaEvent_t event);

/**
 * \brief Make an execution context wait on an event
 *
 * Makes all future work submitted to execution context \p ctx wait for all work
 * captured in \p event. The synchronization will be performed on the device
 * and will not block the calling CPU thread. See ::cudaExecutionCtxRecordEvent()
 * for details on what is captured by an event.
 * If the execution context passed to \p ctx is the device (primary) context obtained via
 * ::cudaDeviceGetExecutionCtx(), all green contexts created on the device will wait for
 * \p event as well.
 *
 * \note \p event may be from a different execution context or device than \p ctx.
 *
 * \note The API will return ::cudaErrorStreamCaptureUnsupported and
 * invalidate the capture if the specified event \p event is part of an ongoing
 * capture sequence or if the specified execution context \p ctx has a stream in the capture mode.
 *
 * \param ctx    - Execution context to wait for (required parameter, see note below)
 * \param event  - Event to wait on
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorCudartUnloading,
 * ::cudaErrorInitializationError,
 * ::cudaErrorInvalidHandle,
 * ::cudaErrorStreamCaptureUnsupported
 * \notefnerr
 * \note_callback
 * \note_cudaExecutionContext_t_required_param
 *
 * \sa
 * ::cudaExecutionCtxRecordEvent,
 * ::cudaStreamWaitEvent,
 * ::cuCtxWaitEvent,
 * ::cuGreenCtxWaitEvent
 */
extern __host__ cudaError_t CUDARTAPI cudaExecutionCtxWaitEvent(cudaExecutionContext_t ctx, cudaEvent_t event);

/**
 * \brief Returns the execution context for a device
 *
 * Returns in \p ctx the execution context for the specified device. This is the device's primary context.
 * The returned context can then be passed to APIs that take in a cudaExecutionContext_t enabling explicit
 * context-based programming without relying on thread-local state.
 *
 * Passing the returned execution context to ::cudaExecutionCtxDestroy() is not allowed and will result in undefined behavior.
 *
 * \param ctx - Returns the device execution context
 * \param device - Device to get the execution context for
 *
 * \return
 * ::cudaSuccess,
 * ::cudaErrorInvalidValue,
 * ::cudaErrorInvalidDevice
 *
 * \sa
 * cudaExecutionCtxGetDevice,
 * cudaExecutionCtxGetId
 */
extern __host__ cudaError_t CUDARTAPI cudaDeviceGetExecutionCtx(cudaExecutionContext_t *ctx, int device);

/** @} */ /* END CUDART_CONTEXT */

/** \cond impl_private */
extern __host__ cudaError_t CUDARTAPI cudaGetExportTable(const void **ppExportTable, const cudaUUID_t *pExportTableId);
/** \endcond impl_private */

/**
 * \defgroup CUDART_HIGHLEVEL C++ API Routines
 *
 * ___MANBRIEF___ C++ high level API functions of the CUDA runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the C++ high level API functions of the CUDA runtime
 * application programming interface. To use these functions, your
 * application needs to be compiled with the \p nvcc compiler.
 *
 * \brief C++-style interface built on top of CUDA runtime API
 */

/**
 * \defgroup CUDART_DRIVER Interactions with the CUDA Driver API
 *
 * ___MANBRIEF___ interactions between CUDA Driver API and CUDA Runtime API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the interactions between the CUDA Driver API and the CUDA Runtime API
 *
 * @{
 *
 * \section CUDART_CUDA_execution_context Execution Contexts
 *
 * The CUDA Runtime provides ::cudaExecutionContext_t as an abstraction over
 * driver-level contexts—specifically, green contexts and the primary context.
 *
 * There are two primary ways to obtain an execution context:
 * - ::cudaDeviceGetExecutionCtx: Returns the execution context that corresponds to the primary context of the specified device.
 * - ::cudaGreenCtxCreate: Creates a green context with the specified resources and returns an execution context.
 *
 * Note: Developers should treat ::cudaExecutionContext_t as an opaque handle and avoid assumptions
 * about its underlying representation. The CUDA Runtime does not provide a way to convert this
 * handle into a ::CUcontext or ::CUgreenCtx.
 *
 *
 * \section CUDART_CUDA_primary Primary Context (aka Device Execution Context)
 *
 * The primary context is the default execution context associated with a device in the Runtime.
 * It can be obtained via a call to ::cudaDeviceGetExecutionCtx(). There is a one-to-one mapping
 * between CUDA devices in the runtime and their primary contexts within a process.
 * 
 * From the CUDA Runtime’s perspective, a device and its primary context are functionally synonymous.
 *
 * Unless explicitly overridden, either by making a different context current via the Driver API
 * (e.g., ::cuCtxSetCurrent()) or by using an explicit execution context handle, the Runtime will
 * implicitly initialize and use the primary context for API calls as needed.
 *
 * \section CUDART_CUDA_init Initialization and Tear-Down
 *
 * Unless an explicit execution context is specified (see “Execution Context Management” for APIs),
 * CUDA Runtime API calls operate on the CUDA Driver ::CUcontext which is current to the calling host thread.
 * If no ::CUcontext is current to the calling thread when a CUDA Runtime API call which requires an active context is made,
 * then the primary context (device execution context) for a device will be selected, made current to the calling thread, and initialized.
 * The context will be initialized using the parameters specified by the CUDA Runtime API functions
 * ::cudaSetDeviceFlags(), 
 * ::cudaD3D9SetDirect3DDevice(), 
 * ::cudaD3D10SetDirect3DDevice(), 
 * ::cudaD3D11SetDirect3DDevice(), 
 * ::cudaGLSetGLDevice(), and
 * ::cudaVDPAUSetVDPAUDevice().
 * Note that these functions will fail with ::cudaErrorSetOnActiveProcess if they are 
 * called when the primary context for the specified device has already been initialized,
 * except for ::cudaSetDeviceFlags() which will simply overwrite the previous settings.
 *
 * The function ::cudaInitDevice() ensures that the primary context is initialized
 * for the requested device but does not make it current to the calling thread.
 *
 * The function ::cudaSetDevice() initializes the primary context for the
 * specified device and makes it current to the calling thread by calling ::cuCtxSetCurrent().
 *
 * Primary contexts will remain active until they are explicitly deinitialized 
 * using ::cudaDeviceReset().  The function ::cudaDeviceReset() will deinitialize the 
 * primary context for the calling thread's current device immediately.  The context 
 * will remain current to all of the threads that it was current to.  The next CUDA 
 * Runtime API call on any thread which requires an active context will trigger the 
 * reinitialization of that device's primary context.
 *
 * Note that primary contexts are shared resources. It is recommended that
 * the primary context not be reset except just before exit or to recover from an
 * unspecified launch failure.
 * 
 * \section CUDART_CUDA_CUcontext CUcontext Interoperability
 *
 * Note that the use of multiple ::CUcontext s per device within a single process 
 * will substantially degrade performance and is strongly discouraged.  Instead,
 * it is highly recommended to either use execution contexts ::cudaExecutionContext_t or the implicit
 * one-to-one device-to-primary context mapping for the process provided by the CUDA Runtime API.
 *
 * If a non-primary ::CUcontext created by the CUDA Driver API is current to a
 * thread then the CUDA Runtime API calls to that thread will operate on that 
 * ::CUcontext, with some exceptions listed below.  Interoperability between data
 * types is discussed in the following sections.
 *
 * The function cudaDeviceEnablePeerAccess() and the rest of the peer access API may not
 * be called when a non-primary CUcontext is current. To use the peer access APIs with a
 * context created using the CUDA Driver API, it is necessary that the CUDA Driver API
 * be used to access these features.
 *
 * All CUDA Runtime API state (e.g, global variables' addresses and values) travels
 * with its underlying ::CUcontext.  In particular, if a ::CUcontext is moved from one 
 * thread to another then all CUDA Runtime API state will move to that thread as well.
 *
 * Please note that attaching to legacy CUcontext (those with a version of 3010 as returned
 * by ::cuCtxGetApiVersion()) is not possible. The CUDA Runtime will return
 * ::cudaErrorIncompatibleDriverContext in such cases.
 *
 * \section CUDART_CUDA_stream Interactions between CUstream and cudaStream_t
 *
 * The types ::CUstream and ::cudaStream_t are identical and may be used interchangeably.
 *
 * \section CUDART_CUDA_event Interactions between CUevent and cudaEvent_t
 *
 * The types ::CUevent and ::cudaEvent_t are identical and may be used interchangeably.
 *
 * \section CUDART_CUDA_array Interactions between CUarray and cudaArray_t 
 *
 * The types ::CUarray and struct ::cudaArray * represent the same data type and may be used
 * interchangeably by casting the two types between each other.
 *
 * In order to use a ::CUarray in a CUDA Runtime API function which takes a struct ::cudaArray *,
 * it is necessary to explicitly cast the ::CUarray to a struct ::cudaArray *.
 *
 * In order to use a struct ::cudaArray * in a CUDA Driver API function which takes a ::CUarray,
 * it is necessary to explicitly cast the struct ::cudaArray * to a ::CUarray .
 *
 * \section CUDART_CUDA_graphicsResource Interactions between CUgraphicsResource and cudaGraphicsResource_t
 *
 * The types ::CUgraphicsResource and ::cudaGraphicsResource_t represent the same data type and may be used
 * interchangeably by casting the two types between each other.
 *
 * In order to use a ::CUgraphicsResource in a CUDA Runtime API function which takes a 
 * ::cudaGraphicsResource_t, it is necessary to explicitly cast the ::CUgraphicsResource 
 * to a ::cudaGraphicsResource_t.
 *
 * In order to use a ::cudaGraphicsResource_t in a CUDA Driver API function which takes a
 * ::CUgraphicsResource, it is necessary to explicitly cast the ::cudaGraphicsResource_t 
 * to a ::CUgraphicsResource.
 *
 * \section CUDART_CUDA_texture_objects Interactions between CUtexObject and cudaTextureObject_t
 *
 * The types ::CUtexObject and ::cudaTextureObject_t represent the same data type and may be used
 * interchangeably by casting the two types between each other.
 *
 * In order to use a ::CUtexObject in a CUDA Runtime API function which takes a ::cudaTextureObject_t,
 * it is necessary to explicitly cast the ::CUtexObject to a ::cudaTextureObject_t.
 *
 * In order to use a ::cudaTextureObject_t in a CUDA Driver API function which takes a ::CUtexObject,
 * it is necessary to explicitly cast the ::cudaTextureObject_t to a ::CUtexObject.
 *
 * \section CUDART_CUDA_surface_objects Interactions between CUsurfObject and cudaSurfaceObject_t
 *
 * The types ::CUsurfObject and ::cudaSurfaceObject_t represent the same data type and may be used
 * interchangeably by casting the two types between each other.
 *
 * In order to use a ::CUsurfObject in a CUDA Runtime API function which takes a ::cudaSurfaceObject_t,
 * it is necessary to explicitly cast the ::CUsurfObject to a ::cudaSurfaceObject_t.
 *
 * In order to use a ::cudaSurfaceObject_t in a CUDA Driver API function which takes a ::CUsurfObject,
 * it is necessary to explicitly cast the ::cudaSurfaceObject_t to a ::CUsurfObject.
 *
 * \section CUDART_CUDA_module Interactions between CUfunction and cudaFunction_t
 *
 * The types ::CUfunction and ::cudaFunction_t represent the same data type and may be used
 * interchangeably by casting the two types between each other.
 *
 * In order to use a ::cudaFunction_t in a CUDA Driver API function which takes a ::CUfunction,
 * it is necessary to explicitly cast the ::cudaFunction_t to a ::CUfunction.
 *
 * \section CUDART_CUDA_library Interactions between CUkernel and cudaKernel_t
 *
 * The types ::CUkernel and ::cudaKernel_t represent the same data type and may be used
 * interchangeably by casting the two types between each other.
 *
 * In order to use a ::cudaKernel_t in a CUDA Driver API function which takes a ::CUkernel,
 * it is necessary to explicitly cast the ::cudaKernel_t to a ::CUkernel.
 *
 */

 /**
  * \brief Get pointer to device entry function that matches entry function \p symbolPtr
  *
  * Returns in \p functionPtr the device entry function corresponding to the symbol \p symbolPtr.
  *
  * \param functionPtr     - Returns the device entry function
  * \param symbolPtr       - Pointer to device entry function to search for
  *
  * \return
  * ::cudaSuccess
  *
  */
extern __host__ cudaError_t CUDARTAPI cudaGetFuncBySymbol(cudaFunction_t* functionPtr, const void* symbolPtr);

/**
 * \brief Get pointer to device kernel that matches entry function \p entryFuncAddr
  *
  * Returns in \p kernelPtr the device kernel corresponding to the entry function \p entryFuncAddr.
  *
  * Note that it is possible that there are multiple symbols belonging to different
  * translation units with the same \p entryFuncAddr registered with this CUDA Runtime
  * and so the order which the translation units are loaded and registered with the
  * CUDA Runtime can lead to differing return pointers in \p kernelPtr .
  * Suggested methods of ensuring uniqueness are to limit visibility of __global__
  * device functions by using static or hidden visibility attribute in the
  * respective translation units.
  *
  * \param kernelPtr          - Returns the device kernel
  * \param entryFuncAddr      - Address of device entry function to search kernel for
  *
  * \return
  * ::cudaSuccess
  *
  * \sa
  * \ref ::cudaGetKernel(cudaKernel_t *kernelPtr, const T *entryFuncAddr) "cudaGetKernel (C++ API)"
  */
extern __host__ cudaError_t CUDARTAPI cudaGetKernel(cudaKernel_t *kernelPtr, const void *entryFuncAddr);

/** @} */ /* END CUDART_DRIVER */

#if defined(__CUDA_API_VERSION_INTERNAL)
    #undef cudaMemcpy
    #undef cudaMemcpyToSymbol
    #undef cudaMemcpyFromSymbol
    #undef cudaMemcpy2D
    #undef cudaMemcpyToArray
    #undef cudaMemcpy2DToArray
    #undef cudaMemcpyFromArray
    #undef cudaMemcpy2DFromArray
    #undef cudaMemcpyArrayToArray
    #undef cudaMemcpy2DArrayToArray
    #undef cudaMemcpy3D
    #undef cudaMemcpy3DPeer
    #undef cudaMemset
    #undef cudaMemset2D
    #undef cudaMemset3D
    #undef cudaMemcpyAsync
    #undef cudaMemcpyToSymbolAsync
    #undef cudaMemcpyFromSymbolAsync
    #undef cudaMemcpy2DAsync
    #undef cudaMemcpyToArrayAsync
    #undef cudaMemcpy2DToArrayAsync
    #undef cudaMemcpyFromArrayAsync
    #undef cudaMemcpy2DFromArrayAsync
    #undef cudaMemcpy3DAsync
    #undef cudaMemcpy3DPeerAsync
    #undef cudaMemcpyBatchAsync
    #undef cudaMemcpy3DBatchAsync
    #undef cudaMemcpyWithAttributesAsync
    #undef cudaMemcpy3DWithAttributesAsync
    #undef cudaMemsetAsync
    #undef cudaMemset2DAsync
    #undef cudaMemset3DAsync
    #undef cudaStreamQuery
    #undef cudaStreamGetDevice
    #undef cudaStreamGetDevResource
    #undef cudaStreamGetFlags
    #undef cudaStreamGetId
    #undef cudaStreamGetPriority
    #undef cudaEventRecord
    #undef cudaEventRecordWithFlags
    #undef cudaStreamWaitEvent
    #undef cudaStreamAddCallback
    #undef cudaStreamAttachMemAsync
    #undef cudaStreamSynchronize
    #undef cudaLaunchKernel
    #undef cudaLaunchKernelExC
    #undef cudaLaunchHostFunc
    #undef cudaLaunchHostFunc_v2
    #undef cudaMemPrefetchAsync
    #undef cudaMemPrefetchBatchAsync
    #undef cudaMemDiscardBatchAsync
    #undef cudaMemDiscardAndPrefetchBatchAsync
    #undef cudaLaunchCooperativeKernel
    #undef cudaSignalExternalSemaphoresAsync
    #undef cudaWaitExternalSemaphoresAsync
    #undef cudaGraphInstantiateWithParams
    #undef cudaGraphUpload
    #undef cudaGraphLaunch
    #undef cudaStreamBeginCapture
    #undef cudaStreamBeginCaptureToGraph
    #undef cudaStreamEndCapture
    #undef cudaStreamIsCapturing
    #undef cudaStreamGetCaptureInfo
    #undef cudaStreamUpdateCaptureDependencies
    #undef cudaStreamCopyAttributes
    #undef cudaStreamGetAttribute
    #undef cudaStreamSetAttribute
    #undef cudaMallocAsync
    #undef cudaFreeAsync
    #undef cudaMallocFromPoolAsync
    #undef cudaGetDriverEntryPoint
    #undef cudaGetDriverEntryPointByVersion


    extern __host__ cudaError_t CUDARTAPI cudaMemcpy(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbol(const void *symbol, const void *src, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbol(void *dst, const void *symbol, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy2D(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromArray(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArray(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t count, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t width, size_t height, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy3D(const struct cudaMemcpy3DParms *p);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeer(const struct cudaMemcpy3DPeerParms *p);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyBatchAsync(void *const *dsts, const void *const *srcs, const size_t *sizes, size_t count, struct cudaMemcpyAttributes *attrs, size_t *attrsIdxs, size_t numAttrs, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DBatchAsync(size_t numOps, struct cudaMemcpy3DBatchOp *opList, unsigned long long flags, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyWithAttributesAsync(void *dst, const void *src, size_t size, struct cudaMemcpyAttributes *attr, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DWithAttributesAsync(struct cudaMemcpy3DBatchOp *op, unsigned long long flags, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemset(void *devPtr, int value, size_t count);
    extern __host__ cudaError_t CUDARTAPI cudaMemset2D(void *devPtr, size_t pitch, int value, size_t width, size_t height);
    extern __host__ cudaError_t CUDARTAPI cudaMemset3D(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpyAsync(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbolAsync(const void *symbol, const void *src, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbolAsync(void *dst, const void *symbol, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy2DAsync(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromArrayAsync(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy3DAsync(const struct cudaMemcpy3DParms *p, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeerAsync(const struct cudaMemcpy3DPeerParms *p, cudaStream_t stream __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemsetAsync(void *devPtr, int value, size_t count, cudaStream_t stream __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset2DAsync(void *devPtr, size_t pitch, int value, size_t width, size_t height, cudaStream_t stream __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset3DAsync(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaStreamQuery(cudaStream_t stream);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetDevice(cudaStream_t hStream, int *device);
    extern __host__ cudaError_t CUDARTAPI cudaStreamGetDevResource(cudaStream_t hStream, cudaDevResource *resource, enum cudaDevResourceType type);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetFlags(cudaStream_t hStream, unsigned int *flags);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetId(cudaStream_t hStream, unsigned long long *streamId);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetPriority(cudaStream_t hStream, int *priority);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecord(cudaEvent_t event, cudaStream_t stream __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecordWithFlags(cudaEvent_t event, cudaStream_t stream __dv(0), unsigned int flags __dv(0));
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamWaitEvent(cudaStream_t stream, cudaEvent_t event, unsigned int flags);
    extern __host__ cudaError_t CUDARTAPI cudaStreamAddCallback(cudaStream_t stream, cudaStreamCallback_t callback, void *userData, unsigned int flags);
    extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamAttachMemAsync(cudaStream_t stream, void *devPtr, size_t length, unsigned int flags);
    extern __host__ cudaError_t CUDARTAPI cudaStreamSynchronize(cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaLaunchKernelExC(const cudaLaunchConfig_t *config, const void *func, void **args);
    extern __host__ cudaError_t CUDARTAPI cudaLaunchCooperativeKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaLaunchHostFunc(cudaStream_t stream, cudaHostFn_t fn, void *userData);
    extern __host__ cudaError_t CUDARTAPI cudaLaunchHostFunc_v2(cudaStream_t stream, cudaHostFn_t fn, void *userData, unsigned int syncMode);
    extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchAsync(const void *devPtr, size_t count, struct cudaMemLocation location, unsigned int flags, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchBatchAsync(void **dptrs, size_t *sizes, size_t count, struct cudaMemLocation *prefetchLocs, size_t *prefetchLocIdxs, size_t numPrefetchLocs, unsigned long long flags, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemDiscardBatchAsync(void **dptrs, size_t *sizes, size_t count, unsigned long long flags, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaMemDiscardAndPrefetchBatchAsync(void **dptrs, size_t *sizes, size_t count, struct cudaMemLocation *prefetchLocs, size_t *prefetchLocIdxs, size_t numPrefetchLocs, unsigned long long flags, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaSignalExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreSignalParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaWaitExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreWaitParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiateWithParams(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, cudaGraphInstantiateParams *instantiateParams);
    extern __host__ cudaError_t CUDARTAPI cudaGraphUpload(cudaGraphExec_t graphExec, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaGraphLaunch(cudaGraphExec_t graphExec, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCapture(cudaStream_t stream, enum cudaStreamCaptureMode mode);
    extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCaptureToGraph(cudaStream_t stream, cudaGraph_t graph, const cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, enum cudaStreamCaptureMode mode);
    extern __host__ cudaError_t CUDARTAPI cudaStreamEndCapture(cudaStream_t stream, cudaGraph_t *pGraph);
    extern __host__ cudaError_t CUDARTAPI cudaStreamIsCapturing(cudaStream_t stream, enum cudaStreamCaptureStatus *pCaptureStatus);
    extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out __dv(0), cudaGraph_t *graph_out __dv(0), const cudaGraphNode_t **dependencies_out __dv(0), const cudaGraphEdgeData **edgeData_out __dv(0), size_t *numDependencies_out __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaStreamUpdateCaptureDependencies(cudaStream_t stream, cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, unsigned int flags __dv(0));
    extern __host__ cudaError_t CUDARTAPI cudaStreamCopyAttributes(cudaStream_t dstStream, cudaStream_t srcStream);
    extern __host__ cudaError_t CUDARTAPI cudaStreamGetAttribute(cudaStream_t stream, cudaStreamAttrID attr, cudaStreamAttrValue *value);
    extern __host__ cudaError_t CUDARTAPI cudaStreamSetAttribute(cudaStream_t stream, cudaStreamAttrID attr, const cudaStreamAttrValue *param);

    extern __host__ cudaError_t CUDARTAPI cudaMallocAsync(void **devPtr, size_t size, cudaStream_t hStream);
    extern __host__ cudaError_t CUDARTAPI cudaFreeAsync(void *devPtr, cudaStream_t hStream);
    extern __host__ cudaError_t CUDARTAPI cudaMallocFromPoolAsync(void **ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream);
    extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPoint(const char *symbol, void **funcPtr, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus);
    extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPointByVersion(const char *symbol, void **funcPtr, unsigned int cudaVersion, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus);


#elif defined(__CUDART_API_PER_THREAD_DEFAULT_STREAM)
    // nvcc stubs reference the 'cudaLaunch'/'cudaLaunchKernel' identifier even if it was defined
    // to 'cudaLaunch_ptsz'/'cudaLaunchKernel_ptsz'. Redirect through a static inline function.
    #undef cudaLaunchKernel
    static __inline__ __host__ cudaError_t cudaLaunchKernel(const void *func, 
                                                            dim3 gridDim, dim3 blockDim, 
                                                            void **args, size_t sharedMem, 
                                                            cudaStream_t stream)
    {
        return cudaLaunchKernel_ptsz(func, gridDim, blockDim, args, sharedMem, stream);
    }
    #define cudaLaunchKernel __CUDART_API_PTSZ(cudaLaunchKernel)
    #undef cudaLaunchKernelExC
    static __inline__ __host__ cudaError_t cudaLaunchKernelExC(const cudaLaunchConfig_t *config,
                                                               const void *func,
                                                                  void **args)
    {
        return cudaLaunchKernelExC_ptsz(config, func, args);
    }
    #define cudaLaunchKernelExC __CUDART_API_PTSZ(cudaLaunchKernelExC)
#endif

#if defined(__cplusplus)
}

#endif /* __cplusplus */

#undef EXCLUDE_FROM_RTC
#endif /* !__CUDACC_RTC__ */

#undef __dv
#undef __CUDA_DEPRECATED

#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_RUNTIME_API_H__)
#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_RUNTIME_API_H__
#endif

#endif /* !__CUDA_RUNTIME_API_H__ */
