Functions

CUresult cuDeviceGet ( CUdevice* device, int  ordinal )

Returns a handle to a compute device.

Parameters

device

- Returned device handle

ordinal

- Device number to get handle for

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns in *device a device handle given an ordinal in the range [0, cuDeviceGetCount()-1].

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGetUuid, cuDeviceGetLuid, cuDeviceTotalMem, cuDeviceGetExecAffinitySupport

CUresult cuDeviceGetAttribute ( int* pi, CUdevice_attribute attrib, CUdevice dev )

Returns information about the device.

Parameters

pi

- Returned device attribute value

attrib

- Device attribute to query

dev

- Device handle

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns in *pi the integer value of the attribute attrib on device dev. The supported attributes are:

• CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK: Maximum number of threads per block;

• CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X: Maximum x-dimension of a block

• CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y: Maximum y-dimension of a block

• CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z: Maximum z-dimension of a block

• CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X: Maximum x-dimension of a grid

• CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y: Maximum y-dimension of a grid

• CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z: Maximum z-dimension of a grid

• CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK: Maximum amount of shared memory available to a thread block in bytes

• CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY: Memory available on device for __constant__ variables in a CUDA C kernel in bytes

• CU_DEVICE_ATTRIBUTE_WARP_SIZE: Warp size in threads

• CU_DEVICE_ATTRIBUTE_MAX_PITCH: Maximum pitch in bytes allowed by the memory copy functions that involve memory regions allocated through cuMemAllocPitch()

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_WIDTH: Maximum 1D texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LINEAR_WIDTH: Maximum width for a 1D texture bound to linear memory

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_MIPMAPPED_WIDTH: Maximum mipmapped 1D texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_WIDTH: Maximum 2D texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_HEIGHT: Maximum 2D texture height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_WIDTH: Maximum width for a 2D texture bound to linear memory

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_HEIGHT: Maximum height for a 2D texture bound to linear memory

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_PITCH: Maximum pitch in bytes for a 2D texture bound to linear memory

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_WIDTH: Maximum mipmapped 2D texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_HEIGHT: Maximum mipmapped 2D texture height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH: Maximum 3D texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT: Maximum 3D texture height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH: Maximum 3D texture depth

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH_ALTERNATE: Alternate maximum 3D texture width, 0 if no alternate maximum 3D texture size is supported

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT_ALTERNATE: Alternate maximum 3D texture height, 0 if no alternate maximum 3D texture size is supported

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH_ALTERNATE: Alternate maximum 3D texture depth, 0 if no alternate maximum 3D texture size is supported

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_WIDTH: Maximum cubemap texture width or height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_WIDTH: Maximum 1D layered texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_LAYERS: Maximum layers in a 1D layered texture

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_WIDTH: Maximum 2D layered texture width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_HEIGHT: Maximum 2D layered texture height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_LAYERS: Maximum layers in a 2D layered texture

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_WIDTH: Maximum cubemap layered texture width or height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_LAYERS: Maximum layers in a cubemap layered texture

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_WIDTH: Maximum 1D surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_WIDTH: Maximum 2D surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_HEIGHT: Maximum 2D surface height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_WIDTH: Maximum 3D surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_HEIGHT: Maximum 3D surface height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_DEPTH: Maximum 3D surface depth

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_WIDTH: Maximum 1D layered surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_LAYERS: Maximum layers in a 1D layered surface

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_WIDTH: Maximum 2D layered surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_HEIGHT: Maximum 2D layered surface height

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_LAYERS: Maximum layers in a 2D layered surface

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_WIDTH: Maximum cubemap surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_WIDTH: Maximum cubemap layered surface width

• CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_LAYERS: Maximum layers in a cubemap layered surface

• CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK: Maximum number of 32-bit registers available to a thread block

• CU_DEVICE_ATTRIBUTE_CLOCK_RATE: The typical clock frequency in kilohertz

• CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT: Alignment requirement; texture base addresses aligned to textureAlign bytes do not need an offset applied to texture fetches

• CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT: Pitch alignment requirement for 2D texture references bound to pitched memory

• CU_DEVICE_ATTRIBUTE_GPU_OVERLAP: 1 if the device can concurrently copy memory between host and device while executing a kernel, or 0 if not

• CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT: Number of multiprocessors on the device

• CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT: 1 if there is a run time limit for kernels executed on the device, or 0 if not

• CU_DEVICE_ATTRIBUTE_INTEGRATED: 1 if the device is integrated with the memory subsystem, or 0 if not

• CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY: 1 if the device can map host memory into the CUDA address space, or 0 if not

• CU_DEVICE_ATTRIBUTE_COMPUTE_MODE: Compute mode that device is currently in. Available modes are as follows:

  • CU_COMPUTEMODE_DEFAULT: Default mode - Device is not restricted and can have multiple CUDA contexts present at a single time.

  • CU_COMPUTEMODE_PROHIBITED: Compute-prohibited mode - Device is prohibited from creating new CUDA contexts.

  • CU_COMPUTEMODE_EXCLUSIVE_PROCESS: Compute-exclusive-process mode - Device can have only one context used by a single process at a time.

• CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS: 1 if the device supports executing multiple kernels within the same context simultaneously, or 0 if not. It is not guaranteed that multiple kernels will be resident on the device concurrently so this feature should not be relied upon for correctness.

• CU_DEVICE_ATTRIBUTE_ECC_ENABLED: 1 if error correction is enabled on the device, 0 if error correction is disabled or not supported by the device

• CU_DEVICE_ATTRIBUTE_PCI_BUS_ID: PCI bus identifier of the device

• CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID: PCI device (also known as slot) identifier of the device

• CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID: PCI domain identifier of the device

• CU_DEVICE_ATTRIBUTE_TCC_DRIVER: 1 if the device is using a TCC driver. TCC is only available on Tesla hardware running Windows Vista or later

• CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE: Peak memory clock frequency in kilohertz

• CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH: Global memory bus width in bits

• CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE: Size of L2 cache in bytes. 0 if the device doesn't have L2 cache

• CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR: Maximum resident threads per multiprocessor

• CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING: 1 if the device shares a unified address space with the host, or 0 if not

• CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR: Major compute capability version number

• CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR: Minor compute capability version number

• CU_DEVICE_ATTRIBUTE_GLOBAL_L1_CACHE_SUPPORTED: 1 if device supports caching globals in L1 cache, 0 if caching globals in L1 cache is not supported by the device

• CU_DEVICE_ATTRIBUTE_LOCAL_L1_CACHE_SUPPORTED: 1 if device supports caching locals in L1 cache, 0 if caching locals in L1 cache is not supported by the device

• CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR: Maximum amount of shared memory available to a multiprocessor in bytes; this amount is shared by all thread blocks simultaneously resident on a multiprocessor

• CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR: Maximum number of 32-bit registers available to a multiprocessor; this number is shared by all thread blocks simultaneously resident on a multiprocessor

• CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY: 1 if device supports allocating managed memory on this system, 0 if allocating managed memory is not supported by the device on this system.

• CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD: 1 if device is on a multi-GPU board, 0 if not.

• CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD_GROUP_ID: Unique identifier for a group of devices associated with the same board. Devices on the same multi-GPU board will share the same identifier.

• CU_DEVICE_ATTRIBUTE_HOST_NATIVE_ATOMIC_SUPPORTED: 1 if Link between the device and the host supports native atomic operations.

• CU_DEVICE_ATTRIBUTE_SINGLE_TO_DOUBLE_PRECISION_PERF_RATIO: Ratio of single precision performance (in floating-point operations per second) to double precision performance.

• CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS: Device supports coherently accessing pageable memory without calling cudaHostRegister on it.

• CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS: Device can coherently access managed memory concurrently with the CPU.

• CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED: Device supports Compute Preemption.

• CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM: Device can access host registered memory at the same virtual address as the CPU.

• CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN: The maximum per block shared memory size supported on this device. This is the maximum value that can be opted into when using the cuFuncSetAttribute() or cuKernelSetAttribute() call. For more details see CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES

• CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES: Device accesses pageable memory via the host's page tables.

• CU_DEVICE_ATTRIBUTE_DIRECT_MANAGED_MEM_ACCESS_FROM_HOST: The host can directly access managed memory on the device without migration.

• CU_DEVICE_ATTRIBUTE_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED: Device supports virtual memory management APIs like cuMemAddressReserve, cuMemCreate, cuMemMap and related APIs

• CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR_SUPPORTED: Device supports exporting memory to a posix file descriptor with cuMemExportToShareableHandle, if requested via cuMemCreate

• CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_WIN32_HANDLE_SUPPORTED: Device supports exporting memory to a Win32 NT handle with cuMemExportToShareableHandle, if requested via cuMemCreate

• CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_WIN32_KMT_HANDLE_SUPPORTED: Device supports exporting memory to a Win32 KMT handle with cuMemExportToShareableHandle, if requested via cuMemCreate

• CU_DEVICE_ATTRIBUTE_MAX_BLOCKS_PER_MULTIPROCESSOR: Maximum number of thread blocks that can reside on a multiprocessor

• CU_DEVICE_ATTRIBUTE_GENERIC_COMPRESSION_SUPPORTED: Device supports compressible memory allocation via cuMemCreate

• CU_DEVICE_ATTRIBUTE_MAX_PERSISTING_L2_CACHE_SIZE: Maximum L2 persisting lines capacity setting in bytes

• CU_DEVICE_ATTRIBUTE_MAX_ACCESS_POLICY_WINDOW_SIZE: Maximum value of CUaccessPolicyWindow::num_bytes

• CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WITH_CUDA_VMM_SUPPORTED: Device supports specifying the GPUDirect RDMA flag with cuMemCreate.

• CU_DEVICE_ATTRIBUTE_RESERVED_SHARED_MEMORY_PER_BLOCK: Amount of shared memory per block reserved by CUDA driver in bytes

• CU_DEVICE_ATTRIBUTE_SPARSE_CUDA_ARRAY_SUPPORTED: Device supports sparse CUDA arrays and sparse CUDA mipmapped arrays.

• CU_DEVICE_ATTRIBUTE_READ_ONLY_HOST_REGISTER_SUPPORTED: Device supports using the cuMemHostRegister flag CU_MEMHOSTERGISTER_READ_ONLY to register memory that must be mapped as read-only to the GPU

• CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED: Device supports using the cuMemAllocAsync and cuMemPool family of APIs

• CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_SUPPORTED: Device supports GPUDirect RDMA APIs, like nvidia_p2p_get_pages (see https://docs.nvidia.com/cuda/gpudirect-rdma for more information)

• CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_FLUSH_WRITES_OPTIONS: The returned attribute shall be interpreted as a bitmask, where the individual bits are described by the CUflushGPUDirectRDMAWritesOptions enum

• CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WRITES_ORDERING: GPUDirect RDMA writes to the device do not need to be flushed for consumers within the scope indicated by the returned attribute. See CUGPUDirectRDMAWritesOrdering for the numerical values returned here.

• CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES: Bitmask of handle types supported with mempool based IPC

• CU_DEVICE_ATTRIBUTE_DEFERRED_MAPPING_CUDA_ARRAY_SUPPORTED: Device supports deferred mapping CUDA arrays and CUDA mipmapped arrays.

• CU_DEVICE_ATTRIBUTE_NUMA_CONFIG: NUMA configuration of a device: value is of type CUdeviceNumaConfig enum

• CU_DEVICE_ATTRIBUTE_NUMA_ID: NUMA node ID of the GPU memory

• CU_DEVICE_ATTRIBUTE_MULTICAST_SUPPORTED: Device supports switch multicast and reduction operations.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetCount, cuDeviceGetName, cuDeviceGetUuid, cuDeviceGet, cuDeviceTotalMem, cuDeviceGetExecAffinitySupport, cudaDeviceGetAttribute, cudaGetDeviceProperties

CUresult cuDeviceGetCount ( int* count )

Returns the number of compute-capable devices.

Parameters

count

- Returned number of compute-capable devices

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE

Description

Returns in *count the number of devices with compute capability greater than or equal to 2.0 that are available for execution. If there is no such device, cuDeviceGetCount() returns 0.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetName, cuDeviceGetUuid, cuDeviceGetLuid, cuDeviceGet, cuDeviceTotalMem, cuDeviceGetExecAffinitySupport, cudaGetDeviceCount

CUresult cuDeviceGetDefaultMemPool ( CUmemoryPool* pool_out, CUdevice dev )

Returns the default mempool of a device.

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZEDCUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE, CUDA_ERROR_NOT_SUPPORTED

Description

The default mempool of a device contains device memory from that device.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuMemAllocAsync, cuMemPoolTrimTo, cuMemPoolGetAttribute, cuMemPoolSetAttribute, cuMemPoolSetAccess, cuDeviceGetMemPool, cuMemPoolCreate

CUresult cuDeviceGetExecAffinitySupport ( int* pi, CUexecAffinityType type, CUdevice dev )

Returns information about the execution affinity support of the device.

Parameters

pi

- 1 if the execution affinity type type is supported by the device, or 0 if not

type

- Execution affinity type to query

dev

- Device handle

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns in *pi whether execution affinity type type is supported by device dev. The supported types are:

• CU_EXEC_AFFINITY_TYPE_SM_COUNT: 1 if context with limited SMs is supported by the device, or 0 if not;

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGetUuid, cuDeviceGet, cuDeviceTotalMem

CUresult cuDeviceGetLuid ( char* luid, unsigned int* deviceNodeMask, CUdevice dev )

Return an LUID and device node mask for the device.

Parameters

luid

- Returned LUID

deviceNodeMask

- Returned device node mask

dev

- Device to get identifier string for

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Return identifying information (luid and deviceNodeMask) to allow matching device with graphics APIs.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGet, cuDeviceTotalMem, cuDeviceGetExecAffinitySupport, cudaGetDeviceProperties

CUresult cuDeviceGetMemPool ( CUmemoryPool* pool, CUdevice dev )

Gets the current mempool for a device.

Returns

CUDA_SUCCESS, CUDA_ERROR_INVALID_VALUE

Description

Returns the last pool provided to cuDeviceSetMemPool for this device or the device's default memory pool if cuDeviceSetMemPool 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.

See also:

cuDeviceGetDefaultMemPool, cuMemPoolCreate, cuDeviceSetMemPool

CUresult cuDeviceGetName ( char* name, int  len, CUdevice dev )

Returns an identifier string for the device.

Parameters

name

- Returned identifier string for the device

len

- Maximum length of string to store in name

dev

- Device to get identifier string for

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns an ASCII string identifying the device dev in the NULL-terminated string pointed to by name. len specifies the maximum length of the string that may be returned.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetUuid, cuDeviceGetLuid, cuDeviceGetCount, cuDeviceGet, cuDeviceTotalMem, cuDeviceGetExecAffinitySupport, cudaGetDeviceProperties

CUresult cuDeviceGetNvSciSyncAttributes ( void* nvSciSyncAttrList, CUdevice dev, int  flags )

Return NvSciSync attributes that this device can support.

Parameters

nvSciSyncAttrList

- Return NvSciSync attributes supported.

dev

- Valid Cuda Device to get NvSciSync attributes for.

flags

- flags describing NvSciSync usage.

Description

Returns in nvSciSyncAttrList, the properties of NvSciSync that this CUDA device, dev can support. The returned nvSciSyncAttrList can be used to create an NvSciSync object that matches this device's capabilities.

If NvSciSyncAttrKey_RequiredPerm field in nvSciSyncAttrList is already set this API will return CUDA_ERROR_INVALID_VALUE.

The applications should set nvSciSyncAttrList to a valid NvSciSyncAttrList failing which this API will return CUDA_ERROR_INVALID_HANDLE.

The flags controls how applications intends to use the NvSciSync created from the nvSciSyncAttrList. The valid flags are:

• CUDA_NVSCISYNC_ATTR_SIGNAL, specifies that the applications intends to signal an NvSciSync on this CUDA device.

• CUDA_NVSCISYNC_ATTR_WAIT, 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 CUDA_ERROR_INVALID_VALUE. 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 nvSciSyncAttrList.

Note that this API updates the input nvSciSyncAttrList with values equivalent to the following public attribute key-values: NvSciSyncAttrKey_RequiredPerm is set to

• NvSciSyncAccessPerm_SignalOnly if CUDA_NVSCISYNC_ATTR_SIGNAL is set in flags.

• NvSciSyncAccessPerm_WaitOnly if CUDA_NVSCISYNC_ATTR_WAIT is set in flags.

• NvSciSyncAccessPerm_WaitSignal if both CUDA_NVSCISYNC_ATTR_WAIT and CUDA_NVSCISYNC_ATTR_SIGNAL are set in flags. NvSciSyncAttrKey_PrimitiveInfo is set to

• NvSciSyncAttrValPrimitiveType_SysmemSemaphore on any valid device.

• NvSciSyncAttrValPrimitiveType_Syncpoint if device is a Tegra device.

• NvSciSyncAttrValPrimitiveType_SysmemSemaphorePayload64b if device is GA10X+. NvSciSyncAttrKey_GpuId is set to the same UUID that is returned for this device from cuDeviceGetUuid.

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_HANDLE, CUDA_ERROR_INVALID_DEVICE, CUDA_ERROR_NOT_SUPPORTED, CUDA_ERROR_OUT_OF_MEMORY

See also:

cuImportExternalSemaphore, cuDestroyExternalSemaphore, cuSignalExternalSemaphoresAsync, cuWaitExternalSemaphoresAsync

CUresult cuDeviceGetTexture1DLinearMaxWidth ( size_t* maxWidthInElements, CUarray_format format, unsigned numChannels, CUdevice dev )

Returns the maximum number of elements allocatable in a 1D linear texture for a given texture element size.

Parameters

maxWidthInElements

- Returned maximum number of texture elements allocatable for given format and numChannels.

format

- Texture format.

numChannels

- Number of channels per texture element.

dev

- Device handle.

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns in maxWidthInElements the maximum number of texture elements allocatable in a 1D linear texture for given format and numChannels.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGetUuid, cuDeviceGet, cudaMemGetInfo, cuDeviceTotalMem

CUresult cuDeviceGetUuid ( CUuuid* uuid, CUdevice dev )

Return an UUID for the device.

Parameters

uuid

- Returned UUID

dev

- Device to get identifier string for

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Note there is a later version of this API, cuDeviceGetUuid_v2. It will supplant this version in 12.0, which is retained for minor version compatibility.

Returns 16-octets identifying the device dev in the structure pointed by the uuid.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetUuid_v2cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGetLuid, cuDeviceGet, cuDeviceTotalMem, cuDeviceGetExecAffinitySupport, cudaGetDeviceProperties

CUresult cuDeviceGetUuid_v2 ( CUuuid* uuid, CUdevice dev )

Return an UUID for the device (11.4+).

Parameters

uuid

- Returned UUID

dev

- Device to get identifier string for

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns 16-octets identifying the device dev in the structure pointed by the uuid. If the device is in MIG mode, returns its MIG UUID which uniquely identifies the subscribed MIG compute instance.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGetLuid, cuDeviceGet, cuDeviceTotalMem, cudaGetDeviceProperties

CUresult cuDeviceSetMemPool ( CUdevice dev, CUmemoryPool pool )

Sets the current memory pool of a device.

Returns

CUDA_SUCCESS, CUDA_ERROR_INVALID_VALUE

Description

The memory pool must be local to the specified device. cuMemAllocAsync 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 cuMemAllocFromPoolAsync to specify asynchronous allocations from a device different than the one the stream runs on.

See also:

cuDeviceGetDefaultMemPool, cuDeviceGetMemPool, cuMemPoolCreate, cuMemPoolDestroy, cuMemAllocFromPoolAsync

CUresult cuDeviceTotalMem ( size_t* bytes, CUdevice dev )

Returns the total amount of memory on the device.

Parameters

bytes

- Returned memory available on device in bytes

dev

- Device handle

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE, CUDA_ERROR_INVALID_DEVICE

Description

Returns in *bytes the total amount of memory available on the device dev in bytes.

Note:

Note that this function may also return error codes from previous, asynchronous launches.

See also:

cuDeviceGetAttribute, cuDeviceGetCount, cuDeviceGetName, cuDeviceGetUuid, cuDeviceGet, cuDeviceGetExecAffinitySupport, cudaMemGetInfo

CUresult cuFlushGPUDirectRDMAWrites ( CUflushGPUDirectRDMAWritesTarget target, CUflushGPUDirectRDMAWritesScope scope )

Blocks until remote writes are visible to the specified scope.

Parameters

target

- The target of the operation, see CUflushGPUDirectRDMAWritesTarget

scope

- The scope of the operation, see CUflushGPUDirectRDMAWritesScope

Returns

CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE,

Description

Blocks until GPUDirect RDMA writes to the target context via mappings created through 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 CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WRITES_ORDERING, 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 CU_DEVICE_ATTRIBUTE_FLUSH_FLUSH_GPU_DIRECT_RDMA_OPTIONS.

Note:

Note that this function may also return error codes from previous, asynchronous launches.