Provided by: nvidia-cuda-dev_9.1.85-3ubuntu1_amd64 
NAME
Data types used by CUDA Runtime -
Data Structures
struct cudaChannelFormatDesc
struct cudaDeviceProp
struct cudaEglFrame
struct cudaEglPlaneDesc
struct cudaExtent
struct cudaFuncAttributes
struct cudaIpcEventHandle_t
struct cudaIpcMemHandle_t
struct cudaLaunchParams
struct cudaMemcpy3DParms
struct cudaMemcpy3DPeerParms
struct cudaPitchedPtr
struct cudaPointerAttributes
struct cudaPos
struct cudaResourceDesc
struct cudaResourceViewDesc
struct cudaTextureDesc
struct surfaceReference
struct textureReference
Defines
#define CUDA_EGL_MAX_PLANES 3
#define CUDA_IPC_HANDLE_SIZE 64
#define cudaArrayCubemap 0x04
#define cudaArrayDefault 0x00
#define cudaArrayLayered 0x01
#define cudaArraySurfaceLoadStore 0x02
#define cudaArrayTextureGather 0x08
#define cudaCooperativeLaunchMultiDeviceNoPostSync 0x02
#define cudaCooperativeLaunchMultiDeviceNoPreSync 0x01
#define cudaCpuDeviceId ((int)-1)
#define cudaDeviceBlockingSync 0x04
#define cudaDeviceLmemResizeToMax 0x10
#define cudaDeviceMapHost 0x08
#define cudaDeviceMask 0x1f
#define cudaDevicePropDontCare
#define cudaDeviceScheduleAuto 0x00
#define cudaDeviceScheduleBlockingSync 0x04
#define cudaDeviceScheduleMask 0x07
#define cudaDeviceScheduleSpin 0x01
#define cudaDeviceScheduleYield 0x02
#define cudaEventBlockingSync 0x01
#define cudaEventDefault 0x00
#define cudaEventDisableTiming 0x02
#define cudaEventInterprocess 0x04
#define cudaHostAllocDefault 0x00
#define cudaHostAllocMapped 0x02
#define cudaHostAllocPortable 0x01
#define cudaHostAllocWriteCombined 0x04
#define cudaHostRegisterDefault 0x00
#define cudaHostRegisterIoMemory 0x04
#define cudaHostRegisterMapped 0x02
#define cudaHostRegisterPortable 0x01
#define cudaInvalidDeviceId ((int)-2)
#define cudaIpcMemLazyEnablePeerAccess 0x01
#define cudaMemAttachGlobal 0x01
#define cudaMemAttachHost 0x02
#define cudaMemAttachSingle 0x04
#define cudaOccupancyDefault 0x00
#define cudaOccupancyDisableCachingOverride 0x01
#define cudaPeerAccessDefault 0x00
#define cudaStreamDefault 0x00
#define cudaStreamLegacy ((cudaStream_t)0x1)
#define cudaStreamNonBlocking 0x01
#define cudaStreamPerThread ((cudaStream_t)0x2)
Typedefs
typedef struct cudaArray * cudaArray_const_t
typedef struct cudaArray * cudaArray_t
typedef struct CUeglStreamConnection_st * cudaEglStreamConnection
typedef enum cudaError cudaError_t
typedef struct CUevent_st * cudaEvent_t
typedef struct cudaGraphicsResource * cudaGraphicsResource_t
typedef struct cudaMipmappedArray * cudaMipmappedArray_const_t
typedef struct cudaMipmappedArray * cudaMipmappedArray_t
typedef enum cudaOutputMode cudaOutputMode_t
typedef struct CUstream_st * cudaStream_t
typedef unsigned long long cudaSurfaceObject_t
typedef unsigned long long cudaTextureObject_t
typedef struct CUuuid_st cudaUUID_t
Enumerations
enum cudaCGScope { cudaCGScopeInvalid = 0, cudaCGScopeGrid = 1, cudaCGScopeMultiGrid =
2 }
enum cudaChannelFormatKind { cudaChannelFormatKindSigned = 0,
cudaChannelFormatKindUnsigned = 1, cudaChannelFormatKindFloat = 2,
cudaChannelFormatKindNone = 3 }
enum cudaComputeMode { cudaComputeModeDefault = 0, cudaComputeModeExclusive = 1,
cudaComputeModeProhibited = 2, cudaComputeModeExclusiveProcess = 3 }
enum cudaDeviceAttr { cudaDevAttrMaxThreadsPerBlock = 1, cudaDevAttrMaxBlockDimX = 2,
cudaDevAttrMaxBlockDimY = 3, cudaDevAttrMaxBlockDimZ = 4, cudaDevAttrMaxGridDimX =
5, cudaDevAttrMaxGridDimY = 6, cudaDevAttrMaxGridDimZ = 7,
cudaDevAttrMaxSharedMemoryPerBlock = 8, cudaDevAttrTotalConstantMemory = 9,
cudaDevAttrWarpSize = 10, cudaDevAttrMaxPitch = 11, cudaDevAttrMaxRegistersPerBlock
= 12, cudaDevAttrClockRate = 13, cudaDevAttrTextureAlignment = 14,
cudaDevAttrGpuOverlap = 15, cudaDevAttrMultiProcessorCount = 16,
cudaDevAttrKernelExecTimeout = 17, cudaDevAttrIntegrated = 18,
cudaDevAttrCanMapHostMemory = 19, cudaDevAttrComputeMode = 20,
cudaDevAttrMaxTexture1DWidth = 21, cudaDevAttrMaxTexture2DWidth = 22,
cudaDevAttrMaxTexture2DHeight = 23, cudaDevAttrMaxTexture3DWidth = 24,
cudaDevAttrMaxTexture3DHeight = 25, cudaDevAttrMaxTexture3DDepth = 26,
cudaDevAttrMaxTexture2DLayeredWidth = 27, cudaDevAttrMaxTexture2DLayeredHeight = 28,
cudaDevAttrMaxTexture2DLayeredLayers = 29, cudaDevAttrSurfaceAlignment = 30,
cudaDevAttrConcurrentKernels = 31, cudaDevAttrEccEnabled = 32, cudaDevAttrPciBusId =
33, cudaDevAttrPciDeviceId = 34, cudaDevAttrTccDriver = 35,
cudaDevAttrMemoryClockRate = 36, cudaDevAttrGlobalMemoryBusWidth = 37,
cudaDevAttrL2CacheSize = 38, cudaDevAttrMaxThreadsPerMultiProcessor = 39,
cudaDevAttrAsyncEngineCount = 40, cudaDevAttrUnifiedAddressing = 41,
cudaDevAttrMaxTexture1DLayeredWidth = 42, cudaDevAttrMaxTexture1DLayeredLayers = 43,
cudaDevAttrMaxTexture2DGatherWidth = 45, cudaDevAttrMaxTexture2DGatherHeight = 46,
cudaDevAttrMaxTexture3DWidthAlt = 47, cudaDevAttrMaxTexture3DHeightAlt = 48,
cudaDevAttrMaxTexture3DDepthAlt = 49, cudaDevAttrPciDomainId = 50,
cudaDevAttrTexturePitchAlignment = 51, cudaDevAttrMaxTextureCubemapWidth = 52,
cudaDevAttrMaxTextureCubemapLayeredWidth = 53,
cudaDevAttrMaxTextureCubemapLayeredLayers = 54, cudaDevAttrMaxSurface1DWidth = 55,
cudaDevAttrMaxSurface2DWidth = 56, cudaDevAttrMaxSurface2DHeight = 57,
cudaDevAttrMaxSurface3DWidth = 58, cudaDevAttrMaxSurface3DHeight = 59,
cudaDevAttrMaxSurface3DDepth = 60, cudaDevAttrMaxSurface1DLayeredWidth = 61,
cudaDevAttrMaxSurface1DLayeredLayers = 62, cudaDevAttrMaxSurface2DLayeredWidth = 63,
cudaDevAttrMaxSurface2DLayeredHeight = 64, cudaDevAttrMaxSurface2DLayeredLayers =
65, cudaDevAttrMaxSurfaceCubemapWidth = 66, cudaDevAttrMaxSurfaceCubemapLayeredWidth
= 67, cudaDevAttrMaxSurfaceCubemapLayeredLayers = 68,
cudaDevAttrMaxTexture1DLinearWidth = 69, cudaDevAttrMaxTexture2DLinearWidth = 70,
cudaDevAttrMaxTexture2DLinearHeight = 71, cudaDevAttrMaxTexture2DLinearPitch = 72,
cudaDevAttrMaxTexture2DMipmappedWidth = 73, cudaDevAttrMaxTexture2DMipmappedHeight =
74, cudaDevAttrComputeCapabilityMajor = 75, cudaDevAttrComputeCapabilityMinor = 76,
cudaDevAttrMaxTexture1DMipmappedWidth = 77, cudaDevAttrStreamPrioritiesSupported =
78, cudaDevAttrGlobalL1CacheSupported = 79, cudaDevAttrLocalL1CacheSupported = 80,
cudaDevAttrMaxSharedMemoryPerMultiprocessor = 81,
cudaDevAttrMaxRegistersPerMultiprocessor = 82, cudaDevAttrManagedMemory = 83,
cudaDevAttrIsMultiGpuBoard = 84, cudaDevAttrMultiGpuBoardGroupID = 85,
cudaDevAttrHostNativeAtomicSupported = 86,
cudaDevAttrSingleToDoublePrecisionPerfRatio = 87, cudaDevAttrPageableMemoryAccess =
88, cudaDevAttrConcurrentManagedAccess = 89, cudaDevAttrComputePreemptionSupported =
90, cudaDevAttrCanUseHostPointerForRegisteredMem = 91, cudaDevAttrCooperativeLaunch =
95, cudaDevAttrCooperativeMultiDeviceLaunch = 96,
cudaDevAttrMaxSharedMemoryPerBlockOptin = 97 }
enum cudaDeviceP2PAttr { cudaDevP2PAttrPerformanceRank = 1, cudaDevP2PAttrAccessSupported
= 2, cudaDevP2PAttrNativeAtomicSupported = 3 }
enum cudaEglColorFormat { cudaEglColorFormatYUV420Planar = 0,
cudaEglColorFormatYUV420SemiPlanar = 1, cudaEglColorFormatYUV422Planar = 2,
cudaEglColorFormatYUV422SemiPlanar = 3, cudaEglColorFormatRGB = 4,
cudaEglColorFormatBGR = 5, cudaEglColorFormatARGB = 6, cudaEglColorFormatRGBA = 7,
cudaEglColorFormatL = 8, cudaEglColorFormatR = 9, cudaEglColorFormatYUV444Planar =
10, cudaEglColorFormatYUV444SemiPlanar = 11, cudaEglColorFormatYUYV422 = 12,
cudaEglColorFormatUYVY422 = 13, cudaEglColorFormatABGR = 14, cudaEglColorFormatBGRA
= 15, cudaEglColorFormatA = 16, cudaEglColorFormatRG = 17, cudaEglColorFormatAYUV =
18, cudaEglColorFormatYVU444SemiPlanar = 19, cudaEglColorFormatYVU422SemiPlanar =
20, cudaEglColorFormatYVU420SemiPlanar = 21,
cudaEglColorFormatY10V10U10_444SemiPlanar = 22,
cudaEglColorFormatY10V10U10_420SemiPlanar = 23,
cudaEglColorFormatY12V12U12_444SemiPlanar = 24,
cudaEglColorFormatY12V12U12_420SemiPlanar = 25, cudaEglColorFormatVYUY_ER = 26,
cudaEglColorFormatUYVY_ER = 27, cudaEglColorFormatYUYV_ER = 28,
cudaEglColorFormatYVYU_ER = 29, cudaEglColorFormatYUV_ER = 30,
cudaEglColorFormatYUVA_ER = 31, cudaEglColorFormatAYUV_ER = 32,
cudaEglColorFormatYUV444Planar_ER = 33, cudaEglColorFormatYUV422Planar_ER = 34,
cudaEglColorFormatYUV420Planar_ER = 35, cudaEglColorFormatYUV444SemiPlanar_ER = 36,
cudaEglColorFormatYUV422SemiPlanar_ER = 37, cudaEglColorFormatYUV420SemiPlanar_ER =
38, cudaEglColorFormatYVU444Planar_ER = 39, cudaEglColorFormatYVU422Planar_ER = 40,
cudaEglColorFormatYVU420Planar_ER = 41, cudaEglColorFormatYVU444SemiPlanar_ER = 42,
cudaEglColorFormatYVU422SemiPlanar_ER = 43, cudaEglColorFormatYVU420SemiPlanar_ER =
44, cudaEglColorFormatBayerRGGB = 45, cudaEglColorFormatBayerBGGR = 46,
cudaEglColorFormatBayerGRBG = 47, cudaEglColorFormatBayerGBRG = 48,
cudaEglColorFormatBayer10RGGB = 49, cudaEglColorFormatBayer10BGGR = 50,
cudaEglColorFormatBayer10GRBG = 51, cudaEglColorFormatBayer10GBRG = 52,
cudaEglColorFormatBayer12RGGB = 53, cudaEglColorFormatBayer12BGGR = 54,
cudaEglColorFormatBayer12GRBG = 55, cudaEglColorFormatBayer12GBRG = 56,
cudaEglColorFormatBayer14RGGB = 57, cudaEglColorFormatBayer14BGGR = 58,
cudaEglColorFormatBayer14GRBG = 59, cudaEglColorFormatBayer14GBRG = 60,
cudaEglColorFormatBayer20RGGB = 61, cudaEglColorFormatBayer20BGGR = 62,
cudaEglColorFormatBayer20GRBG = 63, cudaEglColorFormatBayer20GBRG = 64,
cudaEglColorFormatYVU444Planar = 65, cudaEglColorFormatYVU422Planar = 66,
cudaEglColorFormatYVU420Planar = 67 }
enum cudaEglFrameType { cudaEglFrameTypeArray = 0, cudaEglFrameTypePitch = 1 }
enum cudaEglResourceLocationFlags { cudaEglResourceLocationSysmem = 0x00,
cudaEglResourceLocationVidmem = 0x01 }
enum cudaError { cudaSuccess = 0, cudaErrorMissingConfiguration = 1,
cudaErrorMemoryAllocation = 2, cudaErrorInitializationError = 3,
cudaErrorLaunchFailure = 4, cudaErrorPriorLaunchFailure = 5, cudaErrorLaunchTimeout
= 6, cudaErrorLaunchOutOfResources = 7, cudaErrorInvalidDeviceFunction = 8,
cudaErrorInvalidConfiguration = 9, cudaErrorInvalidDevice = 10,
cudaErrorInvalidValue = 11, cudaErrorInvalidPitchValue = 12, cudaErrorInvalidSymbol
= 13, cudaErrorMapBufferObjectFailed = 14, cudaErrorUnmapBufferObjectFailed = 15,
cudaErrorInvalidHostPointer = 16, cudaErrorInvalidDevicePointer = 17,
cudaErrorInvalidTexture = 18, cudaErrorInvalidTextureBinding = 19,
cudaErrorInvalidChannelDescriptor = 20, cudaErrorInvalidMemcpyDirection = 21,
cudaErrorAddressOfConstant = 22, cudaErrorTextureFetchFailed = 23,
cudaErrorTextureNotBound = 24, cudaErrorSynchronizationError = 25,
cudaErrorInvalidFilterSetting = 26, cudaErrorInvalidNormSetting = 27,
cudaErrorMixedDeviceExecution = 28, cudaErrorCudartUnloading = 29, cudaErrorUnknown
= 30, cudaErrorNotYetImplemented = 31, cudaErrorMemoryValueTooLarge = 32,
cudaErrorInvalidResourceHandle = 33, cudaErrorNotReady = 34,
cudaErrorInsufficientDriver = 35, cudaErrorSetOnActiveProcess = 36,
cudaErrorInvalidSurface = 37, cudaErrorNoDevice = 38, cudaErrorECCUncorrectable =
39, cudaErrorSharedObjectSymbolNotFound = 40, cudaErrorSharedObjectInitFailed = 41,
cudaErrorUnsupportedLimit = 42, cudaErrorDuplicateVariableName = 43,
cudaErrorDuplicateTextureName = 44, cudaErrorDuplicateSurfaceName = 45,
cudaErrorDevicesUnavailable = 46, cudaErrorInvalidKernelImage = 47,
cudaErrorNoKernelImageForDevice = 48, cudaErrorIncompatibleDriverContext = 49,
cudaErrorPeerAccessAlreadyEnabled = 50, cudaErrorPeerAccessNotEnabled = 51,
cudaErrorDeviceAlreadyInUse = 54, cudaErrorProfilerDisabled = 55,
cudaErrorProfilerNotInitialized = 56, cudaErrorProfilerAlreadyStarted = 57,
cudaErrorProfilerAlreadyStopped = 58, cudaErrorAssert = 59, cudaErrorTooManyPeers =
60, cudaErrorHostMemoryAlreadyRegistered = 61, cudaErrorHostMemoryNotRegistered =
62, cudaErrorOperatingSystem = 63, cudaErrorPeerAccessUnsupported = 64,
cudaErrorLaunchMaxDepthExceeded = 65, cudaErrorLaunchFileScopedTex = 66,
cudaErrorLaunchFileScopedSurf = 67, cudaErrorSyncDepthExceeded = 68,
cudaErrorLaunchPendingCountExceeded = 69, cudaErrorNotPermitted = 70,
cudaErrorNotSupported = 71, cudaErrorHardwareStackError = 72,
cudaErrorIllegalInstruction = 73, cudaErrorMisalignedAddress = 74,
cudaErrorInvalidAddressSpace = 75, cudaErrorInvalidPc = 76, cudaErrorIllegalAddress
= 77, cudaErrorInvalidPtx = 78, cudaErrorInvalidGraphicsContext = 79,
cudaErrorNvlinkUncorrectable = 80, cudaErrorJitCompilerNotFound = 81,
cudaErrorCooperativeLaunchTooLarge = 82, cudaErrorStartupFailure = 0x7f,
cudaErrorApiFailureBase = 10000 }
enum cudaFuncAttribute { cudaFuncAttributeMaxDynamicSharedMemorySize = 8,
cudaFuncAttributePreferredSharedMemoryCarveout = 9 }
enum cudaFuncCache { cudaFuncCachePreferNone = 0, cudaFuncCachePreferShared = 1,
cudaFuncCachePreferL1 = 2, cudaFuncCachePreferEqual = 3 }
enum cudaGraphicsCubeFace { cudaGraphicsCubeFacePositiveX = 0x00,
cudaGraphicsCubeFaceNegativeX = 0x01, cudaGraphicsCubeFacePositiveY = 0x02,
cudaGraphicsCubeFaceNegativeY = 0x03, cudaGraphicsCubeFacePositiveZ = 0x04,
cudaGraphicsCubeFaceNegativeZ = 0x05 }
enum cudaGraphicsMapFlags { cudaGraphicsMapFlagsNone = 0, cudaGraphicsMapFlagsReadOnly =
1, cudaGraphicsMapFlagsWriteDiscard = 2 }
enum cudaGraphicsRegisterFlags { cudaGraphicsRegisterFlagsNone = 0,
cudaGraphicsRegisterFlagsReadOnly = 1, cudaGraphicsRegisterFlagsWriteDiscard = 2,
cudaGraphicsRegisterFlagsSurfaceLoadStore = 4, cudaGraphicsRegisterFlagsTextureGather
= 8 }
enum cudaLimit { cudaLimitStackSize = 0x00, cudaLimitPrintfFifoSize = 0x01,
cudaLimitMallocHeapSize = 0x02, cudaLimitDevRuntimeSyncDepth = 0x03,
cudaLimitDevRuntimePendingLaunchCount = 0x04 }
enum cudaMemcpyKind { cudaMemcpyHostToHost = 0, cudaMemcpyHostToDevice = 1,
cudaMemcpyDeviceToHost = 2, cudaMemcpyDeviceToDevice = 3, cudaMemcpyDefault = 4 }
enum cudaMemoryAdvise { cudaMemAdviseSetReadMostly = 1, cudaMemAdviseUnsetReadMostly =
2, cudaMemAdviseSetPreferredLocation = 3, cudaMemAdviseUnsetPreferredLocation = 4,
cudaMemAdviseSetAccessedBy = 5, cudaMemAdviseUnsetAccessedBy = 6 }
enum cudaMemoryType { cudaMemoryTypeHost = 1, cudaMemoryTypeDevice = 2 }
enum cudaMemRangeAttribute { cudaMemRangeAttributeReadMostly = 1,
cudaMemRangeAttributePreferredLocation = 2, cudaMemRangeAttributeAccessedBy = 3,
cudaMemRangeAttributeLastPrefetchLocation = 4 }
enum cudaOutputMode { cudaKeyValuePair = 0x00, cudaCSV = 0x01 }
enum cudaResourceType { cudaResourceTypeArray = 0x00, cudaResourceTypeMipmappedArray =
0x01, cudaResourceTypeLinear = 0x02, cudaResourceTypePitch2D = 0x03 }
enum cudaResourceViewFormat { cudaResViewFormatNone = 0x00,
cudaResViewFormatUnsignedChar1 = 0x01, cudaResViewFormatUnsignedChar2 = 0x02,
cudaResViewFormatUnsignedChar4 = 0x03, cudaResViewFormatSignedChar1 = 0x04,
cudaResViewFormatSignedChar2 = 0x05, cudaResViewFormatSignedChar4 = 0x06,
cudaResViewFormatUnsignedShort1 = 0x07, cudaResViewFormatUnsignedShort2 = 0x08,
cudaResViewFormatUnsignedShort4 = 0x09, cudaResViewFormatSignedShort1 = 0x0a,
cudaResViewFormatSignedShort2 = 0x0b, cudaResViewFormatSignedShort4 = 0x0c,
cudaResViewFormatUnsignedInt1 = 0x0d, cudaResViewFormatUnsignedInt2 = 0x0e,
cudaResViewFormatUnsignedInt4 = 0x0f, cudaResViewFormatSignedInt1 = 0x10,
cudaResViewFormatSignedInt2 = 0x11, cudaResViewFormatSignedInt4 = 0x12,
cudaResViewFormatHalf1 = 0x13, cudaResViewFormatHalf2 = 0x14, cudaResViewFormatHalf4
= 0x15, cudaResViewFormatFloat1 = 0x16, cudaResViewFormatFloat2 = 0x17,
cudaResViewFormatFloat4 = 0x18, cudaResViewFormatUnsignedBlockCompressed1 = 0x19,
cudaResViewFormatUnsignedBlockCompressed2 = 0x1a,
cudaResViewFormatUnsignedBlockCompressed3 = 0x1b,
cudaResViewFormatUnsignedBlockCompressed4 = 0x1c,
cudaResViewFormatSignedBlockCompressed4 = 0x1d,
cudaResViewFormatUnsignedBlockCompressed5 = 0x1e,
cudaResViewFormatSignedBlockCompressed5 = 0x1f,
cudaResViewFormatUnsignedBlockCompressed6H = 0x20,
cudaResViewFormatSignedBlockCompressed6H = 0x21,
cudaResViewFormatUnsignedBlockCompressed7 = 0x22 }
enum cudaSharedCarveout
enum cudaSharedMemConfig
enum cudaSurfaceBoundaryMode { cudaBoundaryModeZero = 0, cudaBoundaryModeClamp = 1,
cudaBoundaryModeTrap = 2 }
enum cudaSurfaceFormatMode { cudaFormatModeForced = 0, cudaFormatModeAuto = 1 }
enum cudaTextureAddressMode { cudaAddressModeWrap = 0, cudaAddressModeClamp = 1,
cudaAddressModeMirror = 2, cudaAddressModeBorder = 3 }
enum cudaTextureFilterMode { cudaFilterModePoint = 0, cudaFilterModeLinear = 1 }
enum cudaTextureReadMode { cudaReadModeElementType = 0, cudaReadModeNormalizedFloat = 1
}
Define Documentation
#define CUDA_EGL_MAX_PLANES 3
Maximum number of planes per frame
#define CUDA_IPC_HANDLE_SIZE 64
CUDA IPC Handle Size
#define cudaArrayCubemap 0x04
Must be set in cudaMalloc3DArray to create a cubemap CUDA array
#define cudaArrayDefault 0x00
Default CUDA array allocation flag
#define cudaArrayLayered 0x01
Must be set in cudaMalloc3DArray to create a layered CUDA array
#define cudaArraySurfaceLoadStore 0x02
Must be set in cudaMallocArray or cudaMalloc3DArray in order to bind surfaces to the CUDA
array
#define cudaArrayTextureGather 0x08
Must be set in cudaMallocArray or cudaMalloc3DArray in order to perform texture gather
operations on the CUDA array
#define cudaCooperativeLaunchMultiDeviceNoPostSync 0x02
If set, any subsequent work pushed in a stream that participated in a call to
cudaLaunchCooperativeKernelMultiDevice will only wait for the kernel launched on the GPU
corresponding to that stream to complete before it begins execution.
#define cudaCooperativeLaunchMultiDeviceNoPreSync 0x01
If set, each kernel launched as part of cudaLaunchCooperativeKernelMultiDevice only waits
for prior work in the stream corresponding to that GPU to complete before the kernel
begins execution.
#define cudaCpuDeviceId ((int)-1)
Device id that represents the CPU
#define cudaDeviceBlockingSync 0x04
Device flag - Use blocking synchronization
Deprecated
This flag was deprecated as of CUDA 4.0 and replaced with
cudaDeviceScheduleBlockingSync.
#define cudaDeviceLmemResizeToMax 0x10
Device flag - Keep local memory allocation after launch
#define cudaDeviceMapHost 0x08
Device flag - Support mapped pinned allocations
#define cudaDeviceMask 0x1f
Device flags mask
#define cudaDevicePropDontCare
Empty device properties
#define cudaDeviceScheduleAuto 0x00
Device flag - Automatic scheduling
#define cudaDeviceScheduleBlockingSync 0x04
Device flag - Use blocking synchronization
#define cudaDeviceScheduleMask 0x07
Device schedule flags mask
#define cudaDeviceScheduleSpin 0x01
Device flag - Spin default scheduling
#define cudaDeviceScheduleYield 0x02
Device flag - Yield default scheduling
#define cudaEventBlockingSync 0x01
Event uses blocking synchronization
#define cudaEventDefault 0x00
Default event flag
#define cudaEventDisableTiming 0x02
Event will not record timing data
#define cudaEventInterprocess 0x04
Event is suitable for interprocess use. cudaEventDisableTiming must be set
#define cudaHostAllocDefault 0x00
Default page-locked allocation flag
#define cudaHostAllocMapped 0x02
Map allocation into device space
#define cudaHostAllocPortable 0x01
Pinned memory accessible by all CUDA contexts
#define cudaHostAllocWriteCombined 0x04
Write-combined memory
#define cudaHostRegisterDefault 0x00
Default host memory registration flag
#define cudaHostRegisterIoMemory 0x04
Memory-mapped I/O space
#define cudaHostRegisterMapped 0x02
Map registered memory into device space
#define cudaHostRegisterPortable 0x01
Pinned memory accessible by all CUDA contexts
#define cudaInvalidDeviceId ((int)-2)
Device id that represents an invalid device
#define cudaIpcMemLazyEnablePeerAccess 0x01
Automatically enable peer access between remote devices as needed
#define cudaMemAttachGlobal 0x01
Memory can be accessed by any stream on any device
#define cudaMemAttachHost 0x02
Memory cannot be accessed by any stream on any device
#define cudaMemAttachSingle 0x04
Memory can only be accessed by a single stream on the associated device
#define cudaOccupancyDefault 0x00
Default behavior
#define cudaOccupancyDisableCachingOverride 0x01
Assume global caching is enabled and cannot be automatically turned off
#define cudaPeerAccessDefault 0x00
Default peer addressing enable flag
#define cudaStreamDefault 0x00
Default stream flag
#define cudaStreamLegacy ((cudaStream_t)0x1)
Legacy stream handle
Stream handle that can be passed as a cudaStream_t to use an implicit stream with legacy
synchronization behavior.
See details of the .
#define cudaStreamNonBlocking 0x01
Stream does not synchronize with stream 0 (the NULL stream)
#define cudaStreamPerThread ((cudaStream_t)0x2)
Per-thread stream handle
Stream handle that can be passed as a cudaStream_t to use an implicit stream with per-
thread synchronization behavior.
See details of the .
Typedef Documentation
typedef struct cudaArray* cudaArray_const_t
CUDA array (as source copy argument)
typedef struct cudaArray* cudaArray_t
CUDA array
typedef struct CUeglStreamConnection_st* cudaEglStreamConnection
CUDA EGLSream Connection
typedef enum cudaError cudaError_t
CUDA Error types
typedef struct CUevent_st* cudaEvent_t
CUDA event types
typedef struct cudaGraphicsResource* cudaGraphicsResource_t
CUDA graphics resource types
typedef struct cudaMipmappedArray* cudaMipmappedArray_const_t
CUDA mipmapped array (as source argument)
typedef struct cudaMipmappedArray* cudaMipmappedArray_t
CUDA mipmapped array
typedef enum cudaOutputMode cudaOutputMode_t
CUDA output file modes
typedef struct CUstream_st* cudaStream_t
CUDA stream
typedef unsigned long long cudaSurfaceObject_t
An opaque value that represents a CUDA Surface object
typedef unsigned long long cudaTextureObject_t
An opaque value that represents a CUDA texture object
typedef struct CUuuid_st cudaUUID_t
CUDA UUID types
Enumeration Type Documentation
enum cudaCGScope
CUDA cooperative group scope
Enumerator:
cudaCGScopeInvalid
Invalid cooperative group scope
cudaCGScopeGrid
Scope represented by a grid_group
cudaCGScopeMultiGrid
Scope represented by a multi_grid_group
enum cudaChannelFormatKind
Channel format kind
Enumerator:
cudaChannelFormatKindSigned
Signed channel format
cudaChannelFormatKindUnsigned
Unsigned channel format
cudaChannelFormatKindFloat
Float channel format
cudaChannelFormatKindNone
No channel format
enum cudaComputeMode
CUDA device compute modes
Enumerator:
cudaComputeModeDefault
Default compute mode (Multiple threads can use cudaSetDevice() with this device)
cudaComputeModeExclusive
Compute-exclusive-thread mode (Only one thread in one process will be able to use
cudaSetDevice() with this device)
cudaComputeModeProhibited
Compute-prohibited mode (No threads can use cudaSetDevice() with this device)
cudaComputeModeExclusiveProcess
Compute-exclusive-process mode (Many threads in one process will be able to use
cudaSetDevice() with this device)
enum cudaDeviceAttr
CUDA device attributes
Enumerator:
cudaDevAttrMaxThreadsPerBlock
Maximum number of threads per block
cudaDevAttrMaxBlockDimX
Maximum block dimension X
cudaDevAttrMaxBlockDimY
Maximum block dimension Y
cudaDevAttrMaxBlockDimZ
Maximum block dimension Z
cudaDevAttrMaxGridDimX
Maximum grid dimension X
cudaDevAttrMaxGridDimY
Maximum grid dimension Y
cudaDevAttrMaxGridDimZ
Maximum grid dimension Z
cudaDevAttrMaxSharedMemoryPerBlock
Maximum shared memory available per block in bytes
cudaDevAttrTotalConstantMemory
Memory available on device for __constant__ variables in a CUDA C kernel in bytes
cudaDevAttrWarpSize
Warp size in threads
cudaDevAttrMaxPitch
Maximum pitch in bytes allowed by memory copies
cudaDevAttrMaxRegistersPerBlock
Maximum number of 32-bit registers available per block
cudaDevAttrClockRate
Peak clock frequency in kilohertz
cudaDevAttrTextureAlignment
Alignment requirement for textures
cudaDevAttrGpuOverlap
Device can possibly copy memory and execute a kernel concurrently
cudaDevAttrMultiProcessorCount
Number of multiprocessors on device
cudaDevAttrKernelExecTimeout
Specifies whether there is a run time limit on kernels
cudaDevAttrIntegrated
Device is integrated with host memory
cudaDevAttrCanMapHostMemory
Device can map host memory into CUDA address space
cudaDevAttrComputeMode
Compute mode (See cudaComputeMode for details)
cudaDevAttrMaxTexture1DWidth
Maximum 1D texture width
cudaDevAttrMaxTexture2DWidth
Maximum 2D texture width
cudaDevAttrMaxTexture2DHeight
Maximum 2D texture height
cudaDevAttrMaxTexture3DWidth
Maximum 3D texture width
cudaDevAttrMaxTexture3DHeight
Maximum 3D texture height
cudaDevAttrMaxTexture3DDepth
Maximum 3D texture depth
cudaDevAttrMaxTexture2DLayeredWidth
Maximum 2D layered texture width
cudaDevAttrMaxTexture2DLayeredHeight
Maximum 2D layered texture height
cudaDevAttrMaxTexture2DLayeredLayers
Maximum layers in a 2D layered texture
cudaDevAttrSurfaceAlignment
Alignment requirement for surfaces
cudaDevAttrConcurrentKernels
Device can possibly execute multiple kernels concurrently
cudaDevAttrEccEnabled
Device has ECC support enabled
cudaDevAttrPciBusId
PCI bus ID of the device
cudaDevAttrPciDeviceId
PCI device ID of the device
cudaDevAttrTccDriver
Device is using TCC driver model
cudaDevAttrMemoryClockRate
Peak memory clock frequency in kilohertz
cudaDevAttrGlobalMemoryBusWidth
Global memory bus width in bits
cudaDevAttrL2CacheSize
Size of L2 cache in bytes
cudaDevAttrMaxThreadsPerMultiProcessor
Maximum resident threads per multiprocessor
cudaDevAttrAsyncEngineCount
Number of asynchronous engines
cudaDevAttrUnifiedAddressing
Device shares a unified address space with the host
cudaDevAttrMaxTexture1DLayeredWidth
Maximum 1D layered texture width
cudaDevAttrMaxTexture1DLayeredLayers
Maximum layers in a 1D layered texture
cudaDevAttrMaxTexture2DGatherWidth
Maximum 2D texture width if cudaArrayTextureGather is set
cudaDevAttrMaxTexture2DGatherHeight
Maximum 2D texture height if cudaArrayTextureGather is set
cudaDevAttrMaxTexture3DWidthAlt
Alternate maximum 3D texture width
cudaDevAttrMaxTexture3DHeightAlt
Alternate maximum 3D texture height
cudaDevAttrMaxTexture3DDepthAlt
Alternate maximum 3D texture depth
cudaDevAttrPciDomainId
PCI domain ID of the device
cudaDevAttrTexturePitchAlignment
Pitch alignment requirement for textures
cudaDevAttrMaxTextureCubemapWidth
Maximum cubemap texture width/height
cudaDevAttrMaxTextureCubemapLayeredWidth
Maximum cubemap layered texture width/height
cudaDevAttrMaxTextureCubemapLayeredLayers
Maximum layers in a cubemap layered texture
cudaDevAttrMaxSurface1DWidth
Maximum 1D surface width
cudaDevAttrMaxSurface2DWidth
Maximum 2D surface width
cudaDevAttrMaxSurface2DHeight
Maximum 2D surface height
cudaDevAttrMaxSurface3DWidth
Maximum 3D surface width
cudaDevAttrMaxSurface3DHeight
Maximum 3D surface height
cudaDevAttrMaxSurface3DDepth
Maximum 3D surface depth
cudaDevAttrMaxSurface1DLayeredWidth
Maximum 1D layered surface width
cudaDevAttrMaxSurface1DLayeredLayers
Maximum layers in a 1D layered surface
cudaDevAttrMaxSurface2DLayeredWidth
Maximum 2D layered surface width
cudaDevAttrMaxSurface2DLayeredHeight
Maximum 2D layered surface height
cudaDevAttrMaxSurface2DLayeredLayers
Maximum layers in a 2D layered surface
cudaDevAttrMaxSurfaceCubemapWidth
Maximum cubemap surface width
cudaDevAttrMaxSurfaceCubemapLayeredWidth
Maximum cubemap layered surface width
cudaDevAttrMaxSurfaceCubemapLayeredLayers
Maximum layers in a cubemap layered surface
cudaDevAttrMaxTexture1DLinearWidth
Maximum 1D linear texture width
cudaDevAttrMaxTexture2DLinearWidth
Maximum 2D linear texture width
cudaDevAttrMaxTexture2DLinearHeight
Maximum 2D linear texture height
cudaDevAttrMaxTexture2DLinearPitch
Maximum 2D linear texture pitch in bytes
cudaDevAttrMaxTexture2DMipmappedWidth
Maximum mipmapped 2D texture width
cudaDevAttrMaxTexture2DMipmappedHeight
Maximum mipmapped 2D texture height
cudaDevAttrComputeCapabilityMajor
Major compute capability version number
cudaDevAttrComputeCapabilityMinor
Minor compute capability version number
cudaDevAttrMaxTexture1DMipmappedWidth
Maximum mipmapped 1D texture width
cudaDevAttrStreamPrioritiesSupported
Device supports stream priorities
cudaDevAttrGlobalL1CacheSupported
Device supports caching globals in L1
cudaDevAttrLocalL1CacheSupported
Device supports caching locals in L1
cudaDevAttrMaxSharedMemoryPerMultiprocessor
Maximum shared memory available per multiprocessor in bytes
cudaDevAttrMaxRegistersPerMultiprocessor
Maximum number of 32-bit registers available per multiprocessor
cudaDevAttrManagedMemory
Device can allocate managed memory on this system
cudaDevAttrIsMultiGpuBoard
Device is on a multi-GPU board
cudaDevAttrMultiGpuBoardGroupID
Unique identifier for a group of devices on the same multi-GPU board
cudaDevAttrHostNativeAtomicSupported
Link between the device and the host supports native atomic operations
cudaDevAttrSingleToDoublePrecisionPerfRatio
Ratio of single precision performance (in floating-point operations per second) to
double precision performance
cudaDevAttrPageableMemoryAccess
Device supports coherently accessing pageable memory without calling
cudaHostRegister on it
cudaDevAttrConcurrentManagedAccess
Device can coherently access managed memory concurrently with the CPU
cudaDevAttrComputePreemptionSupported
Device supports Compute Preemption
cudaDevAttrCanUseHostPointerForRegisteredMem
Device can access host registered memory at the same virtual address as the CPU
cudaDevAttrCooperativeLaunch
Device supports launching cooperative kernels via cudaLaunchCooperativeKernel
cudaDevAttrCooperativeMultiDeviceLaunch
Device can participate in cooperative kernels launched via
cudaLaunchCooperativeKernelMultiDevice
cudaDevAttrMaxSharedMemoryPerBlockOptin
The maximum optin shared memory per block. This value may vary by chip. See
cudaFuncSetAttribute
enum cudaDeviceP2PAttr
CUDA device P2P attributes
Enumerator:
cudaDevP2PAttrPerformanceRank
A relative value indicating the performance of the link between two devices
cudaDevP2PAttrAccessSupported
Peer access is enabled
cudaDevP2PAttrNativeAtomicSupported
Native atomic operation over the link supported
enum cudaEglColorFormat
CUDA EGL Color Format - The different planar and multiplanar formats currently supported
for CUDA_EGL interops.
Enumerator:
cudaEglColorFormatYUV420Planar
Y, U, V in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V
height = 1/2 Y height.
cudaEglColorFormatYUV420SemiPlanar
Y, UV in two surfaces (UV as one surface), width, height ratio same as
YUV420Planar.
cudaEglColorFormatYUV422Planar
Y, U, V each in a separate surface, U/V width = 1/2 Y width, U/V height = Y height.
cudaEglColorFormatYUV422SemiPlanar
Y, UV in two surfaces, width, height ratio same as YUV422Planar.
cudaEglColorFormatRGB
R/G/B three channels in one surface with RGB byte ordering.
cudaEglColorFormatBGR
R/G/B three channels in one surface with BGR byte ordering.
cudaEglColorFormatARGB
R/G/B/A four channels in one surface with ARGB byte ordering.
cudaEglColorFormatRGBA
R/G/B/A four channels in one surface with RGBA byte ordering.
cudaEglColorFormatL
single luminance channel in one surface.
cudaEglColorFormatR
single color channel in one surface.
cudaEglColorFormatYUV444Planar
Y, U, V in three surfaces, each in a separate surface, U/V width = Y width, U/V
height = Y height.
cudaEglColorFormatYUV444SemiPlanar
Y, UV in two surfaces (UV as one surface), width, height ratio same as
YUV444Planar.
cudaEglColorFormatYUYV422
Y, U, V in one surface, interleaved as YUYV.
cudaEglColorFormatUYVY422
Y, U, V in one surface, interleaved as UYVY.
cudaEglColorFormatABGR
R/G/B/A four channels in one surface with ABGR byte ordering.
cudaEglColorFormatBGRA
R/G/B/A four channels in one surface with BGRA byte ordering.
cudaEglColorFormatA
Alpha color format - one channel in one surface.
cudaEglColorFormatRG
R/G color format - two channels in one surface with RG byte ordering
cudaEglColorFormatAYUV
Y, U, V, A four channels in one surface, interleaved as AYUV.
cudaEglColorFormatYVU444SemiPlanar
Y, VU in two surfaces (VU as one surface), U/V width = Y width, U/V height = Y
height.
cudaEglColorFormatYVU422SemiPlanar
Y, VU in two surfaces (VU as one surface), U/V width = 1/2 Y width, U/V height = Y
height.
cudaEglColorFormatYVU420SemiPlanar
Y, VU in two surfaces (VU as one surface), U/V width = 1/2 Y width, U/V height =
1/2 Y height.
cudaEglColorFormatY10V10U10_444SemiPlanar
Y10, V10U10 in two surfaces (VU as one surface), U/V width = Y width, U/V height =
Y height.
cudaEglColorFormatY10V10U10_420SemiPlanar
Y10, V10U10 in two surfaces (VU as one surface), U/V width = 1/2 Y width, U/V
height = 1/2 Y height.
cudaEglColorFormatY12V12U12_444SemiPlanar
Y12, V12U12 in two surfaces (VU as one surface), U/V width = Y width, U/V height =
Y height.
cudaEglColorFormatY12V12U12_420SemiPlanar
Y12, V12U12 in two surfaces (VU as one surface), U/V width = 1/2 Y width, U/V
height = 1/2 Y height.
cudaEglColorFormatVYUY_ER
Extended Range Y, U, V in one surface, interleaved as VYUY.
cudaEglColorFormatUYVY_ER
Extended Range Y, U, V in one surface, interleaved as UYVY.
cudaEglColorFormatYUYV_ER
Extended Range Y, U, V in one surface, interleaved as YUYV.
cudaEglColorFormatYVYU_ER
Extended Range Y, U, V in one surface, interleaved as YVYU.
cudaEglColorFormatYUV_ER
Extended Range Y, U, V three channels in one surface, interleaved as YUV.
cudaEglColorFormatYUVA_ER
Extended Range Y, U, V, A four channels in one surface, interleaved as YUVA.
cudaEglColorFormatAYUV_ER
Extended Range Y, U, V, A four channels in one surface, interleaved as AYUV.
cudaEglColorFormatYUV444Planar_ER
Extended Range Y, U, V in three surfaces, U/V width = Y width, U/V height = Y
height.
cudaEglColorFormatYUV422Planar_ER
Extended Range Y, U, V in three surfaces, U/V width = 1/2 Y width, U/V height = Y
height.
cudaEglColorFormatYUV420Planar_ER
Extended Range Y, U, V in three surfaces, U/V width = 1/2 Y width, U/V height = 1/2
Y height.
cudaEglColorFormatYUV444SemiPlanar_ER
Extended Range Y, UV in two surfaces (UV as one surface), U/V width = Y width, U/V
height = Y height.
cudaEglColorFormatYUV422SemiPlanar_ER
Extended Range Y, UV in two surfaces (UV as one surface), U/V width = 1/2 Y width,
U/V height = Y height.
cudaEglColorFormatYUV420SemiPlanar_ER
Extended Range Y, UV in two surfaces (UV as one surface), U/V width = 1/2 Y width,
U/V height = 1/2 Y height.
cudaEglColorFormatYVU444Planar_ER
Extended Range Y, V, U in three surfaces, U/V width = Y width, U/V height = Y
height.
cudaEglColorFormatYVU422Planar_ER
Extended Range Y, V, U in three surfaces, U/V width = 1/2 Y width, U/V height = Y
height.
cudaEglColorFormatYVU420Planar_ER
Extended Range Y, V, U in three surfaces, U/V width = 1/2 Y width, U/V height = 1/2
Y height.
cudaEglColorFormatYVU444SemiPlanar_ER
Extended Range Y, VU in two surfaces (VU as one surface), U/V width = Y width, U/V
height = Y height.
cudaEglColorFormatYVU422SemiPlanar_ER
Extended Range Y, VU in two surfaces (VU as one surface), U/V width = 1/2 Y width,
U/V height = Y height.
cudaEglColorFormatYVU420SemiPlanar_ER
Extended Range Y, VU in two surfaces (VU as one surface), U/V width = 1/2 Y width,
U/V height = 1/2 Y height.
cudaEglColorFormatBayerRGGB
Bayer format - one channel in one surface with interleaved RGGB ordering.
cudaEglColorFormatBayerBGGR
Bayer format - one channel in one surface with interleaved BGGR ordering.
cudaEglColorFormatBayerGRBG
Bayer format - one channel in one surface with interleaved GRBG ordering.
cudaEglColorFormatBayerGBRG
Bayer format - one channel in one surface with interleaved GBRG ordering.
cudaEglColorFormatBayer10RGGB
Bayer10 format - one channel in one surface with interleaved RGGB ordering. 10 bits
used 6 bits No-op.
cudaEglColorFormatBayer10BGGR
Bayer10 format - one channel in one surface with interleaved BGGR ordering. 10 bits
used 6 bits No-op.
cudaEglColorFormatBayer10GRBG
Bayer10 format - one channel in one surface with interleaved GRBG ordering. 10 bits
used 6 bits No-op.
cudaEglColorFormatBayer10GBRG
Bayer10 format - one channel in one surface with interleaved GBRG ordering. 10 bits
used 6 bits No-op.
cudaEglColorFormatBayer12RGGB
Bayer12 format - one channel in one surface with interleaved RGGB ordering. 12 bits
used 4 bits No-op.
cudaEglColorFormatBayer12BGGR
Bayer12 format - one channel in one surface with interleaved BGGR ordering. 12 bits
used 4 bits No-op.
cudaEglColorFormatBayer12GRBG
Bayer12 format - one channel in one surface with interleaved GRBG ordering. 12 bits
used 4 bits No-op.
cudaEglColorFormatBayer12GBRG
Bayer12 format - one channel in one surface with interleaved GBRG ordering. 12 bits
used 4 bits No-op.
cudaEglColorFormatBayer14RGGB
Bayer14 format - one channel in one surface with interleaved RGGB ordering. 14 bits
used 2 bits No-op.
cudaEglColorFormatBayer14BGGR
Bayer14 format - one channel in one surface with interleaved BGGR ordering. 14 bits
used 2 bits No-op.
cudaEglColorFormatBayer14GRBG
Bayer14 format - one channel in one surface with interleaved GRBG ordering. 14 bits
used 2 bits No-op.
cudaEglColorFormatBayer14GBRG
Bayer14 format - one channel in one surface with interleaved GBRG ordering. 14 bits
used 2 bits No-op.
cudaEglColorFormatBayer20RGGB
Bayer20 format - one channel in one surface with interleaved RGGB ordering. 20 bits
used 12 bits No-op.
cudaEglColorFormatBayer20BGGR
Bayer20 format - one channel in one surface with interleaved BGGR ordering. 20 bits
used 12 bits No-op.
cudaEglColorFormatBayer20GRBG
Bayer20 format - one channel in one surface with interleaved GRBG ordering. 20 bits
used 12 bits No-op.
cudaEglColorFormatBayer20GBRG
Bayer20 format - one channel in one surface with interleaved GBRG ordering. 20 bits
used 12 bits No-op.
cudaEglColorFormatYVU444Planar
Y, V, U in three surfaces, each in a separate surface, U/V width = Y width, U/V
height = Y height.
cudaEglColorFormatYVU422Planar
Y, V, U in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V
height = Y height.
cudaEglColorFormatYVU420Planar
Y, V, U in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V
height = 1/2 Y height.
enum cudaEglFrameType
CUDA EglFrame type - array or pointer
Enumerator:
cudaEglFrameTypeArray
Frame type CUDA array
cudaEglFrameTypePitch
Frame type CUDA pointer
enum cudaEglResourceLocationFlags
Resource location flags- sysmem or vidmem
For CUDA context on iGPU, since video and system memory are equivalent - these flags will
not have an effect on the execution.
For CUDA context on dGPU, applications can use the flag cudaEglResourceLocationFlags to
give a hint about the desired location.
cudaEglResourceLocationSysmem - the frame data is made resident on the system memory to be
accessed by CUDA.
cudaEglResourceLocationVidmem - the frame data is made resident on the dedicated video
memory to be accessed by CUDA.
There may be an additional latency due to new allocation and data migration, if the frame
is produced on a different memory.
Enumerator:
cudaEglResourceLocationSysmem
Resource location sysmem
cudaEglResourceLocationVidmem
Resource location vidmem
enum cudaError
CUDA error types
Enumerator:
cudaSuccess
The API call returned with no errors. In the case of query calls, this can also
mean that the operation being queried is complete (see cudaEventQuery() and
cudaStreamQuery()).
cudaErrorMissingConfiguration
The device function being invoked (usually via cudaLaunchKernel()) was not
previously configured via the cudaConfigureCall() function.
cudaErrorMemoryAllocation
The API call failed because it was unable to allocate enough memory to perform the
requested operation.
cudaErrorInitializationError
The API call failed because the CUDA driver and runtime could not be initialized.
cudaErrorLaunchFailure
An exception occurred on the device while executing a kernel. Common causes include
dereferencing an invalid device pointer and accessing out of bounds shared memory.
The device cannot be used until cudaThreadExit() is called. All existing device
memory allocations are invalid and must be reconstructed if the program is to
continue using CUDA.
cudaErrorPriorLaunchFailure
This indicated that a previous kernel launch failed. This was previously used for
device emulation of kernel launches.
Deprecated
This error return is deprecated as of CUDA 3.1. Device emulation mode was removed with
the CUDA 3.1 release.
cudaErrorLaunchTimeout
This indicates that the device kernel took too long to execute. This can only occur
if timeouts are enabled - see the device property kernelExecTimeoutEnabled for more
information. This leaves the process in an inconsistent state and any further CUDA
work will return the same error. To continue using CUDA, the process must be
terminated and relaunched.
cudaErrorLaunchOutOfResources
This indicates that a launch did not occur because it did not have appropriate
resources. Although this error is similar to cudaErrorInvalidConfiguration, this
error usually indicates that the user has attempted to pass too many arguments to
the device kernel, or the kernel launch specifies too many threads for the kernel's
register count.
cudaErrorInvalidDeviceFunction
The requested device function does not exist or is not compiled for the proper
device architecture.
cudaErrorInvalidConfiguration
This indicates that a kernel launch is requesting resources that can never be
satisfied by the current device. Requesting more shared memory per block than the
device supports will trigger this error, as will requesting too many threads or
blocks. See cudaDeviceProp for more device limitations.
cudaErrorInvalidDevice
This indicates that the device ordinal supplied by the user does not correspond to
a valid CUDA device.
cudaErrorInvalidValue
This indicates that one or more of the parameters passed to the API call is not
within an acceptable range of values.
cudaErrorInvalidPitchValue
This indicates that one or more of the pitch-related parameters passed to the API
call is not within the acceptable range for pitch.
cudaErrorInvalidSymbol
This indicates that the symbol name/identifier passed to the API call is not a
valid name or identifier.
cudaErrorMapBufferObjectFailed
This indicates that the buffer object could not be mapped.
cudaErrorUnmapBufferObjectFailed
This indicates that the buffer object could not be unmapped.
cudaErrorInvalidHostPointer
This indicates that at least one host pointer passed to the API call is not a valid
host pointer.
cudaErrorInvalidDevicePointer
This indicates that at least one device pointer passed to the API call is not a
valid device pointer.
cudaErrorInvalidTexture
This indicates that the texture passed to the API call is not a valid texture.
cudaErrorInvalidTextureBinding
This indicates that the texture binding is not valid. This occurs if you call
cudaGetTextureAlignmentOffset() with an unbound texture.
cudaErrorInvalidChannelDescriptor
This indicates that the channel descriptor passed to the API call is not valid.
This occurs if the format is not one of the formats specified by
cudaChannelFormatKind, or if one of the dimensions is invalid.
cudaErrorInvalidMemcpyDirection
This indicates that the direction of the memcpy passed to the API call is not one
of the types specified by cudaMemcpyKind.
cudaErrorAddressOfConstant
This indicated that the user has taken the address of a constant variable, which
was forbidden up until the CUDA 3.1 release.
Deprecated
This error return is deprecated as of CUDA 3.1. Variables in constant memory may now
have their address taken by the runtime via cudaGetSymbolAddress().
cudaErrorTextureFetchFailed
This indicated that a texture fetch was not able to be performed. This was
previously used for device emulation of texture operations.
Deprecated
This error return is deprecated as of CUDA 3.1. Device emulation mode was removed with
the CUDA 3.1 release.
cudaErrorTextureNotBound
This indicated that a texture was not bound for access. This was previously used
for device emulation of texture operations.
Deprecated
This error return is deprecated as of CUDA 3.1. Device emulation mode was removed with
the CUDA 3.1 release.
cudaErrorSynchronizationError
This indicated that a synchronization operation had failed. This was previously
used for some device emulation functions.
Deprecated
This error return is deprecated as of CUDA 3.1. Device emulation mode was removed with
the CUDA 3.1 release.
cudaErrorInvalidFilterSetting
This indicates that a non-float texture was being accessed with linear filtering.
This is not supported by CUDA.
cudaErrorInvalidNormSetting
This indicates that an attempt was made to read a non-float texture as a normalized
float. This is not supported by CUDA.
cudaErrorMixedDeviceExecution
Mixing of device and device emulation code was not allowed.
Deprecated
This error return is deprecated as of CUDA 3.1. Device emulation mode was removed with
the CUDA 3.1 release.
cudaErrorCudartUnloading
This indicates that a CUDA Runtime API call cannot be executed because it is being
called during process shut down, at a point in time after CUDA driver has been
unloaded.
cudaErrorUnknown
This indicates that an unknown internal error has occurred.
cudaErrorNotYetImplemented
This indicates that the API call is not yet implemented. Production releases of
CUDA will never return this error.
Deprecated
This error return is deprecated as of CUDA 4.1.
cudaErrorMemoryValueTooLarge
This indicated that an emulated device pointer exceeded the 32-bit address range.
Deprecated
This error return is deprecated as of CUDA 3.1. Device emulation mode was removed with
the CUDA 3.1 release.
cudaErrorInvalidResourceHandle
This indicates that a resource handle passed to the API call was not valid.
Resource handles are opaque types like cudaStream_t and cudaEvent_t.
cudaErrorNotReady
This indicates that asynchronous operations issued previously have not completed
yet. This result is not actually an error, but must be indicated differently than
cudaSuccess (which indicates completion). Calls that may return this value include
cudaEventQuery() and cudaStreamQuery().
cudaErrorInsufficientDriver
This indicates that the installed NVIDIA CUDA driver is older than the CUDA runtime
library. This is not a supported configuration. Users should install an updated
NVIDIA display driver to allow the application to run.
cudaErrorSetOnActiveProcess
This indicates that the user has called cudaSetValidDevices(),
cudaSetDeviceFlags(), cudaD3D9SetDirect3DDevice(), cudaD3D10SetDirect3DDevice,
cudaD3D11SetDirect3DDevice(), or cudaVDPAUSetVDPAUDevice() after initializing the
CUDA runtime by calling non-device management operations (allocating memory and
launching kernels are examples of non-device management operations). This error can
also be returned if using runtime/driver interoperability and there is an existing
CUcontext active on the host thread.
cudaErrorInvalidSurface
This indicates that the surface passed to the API call is not a valid surface.
cudaErrorNoDevice
This indicates that no CUDA-capable devices were detected by the installed CUDA
driver.
cudaErrorECCUncorrectable
This indicates that an uncorrectable ECC error was detected during execution.
cudaErrorSharedObjectSymbolNotFound
This indicates that a link to a shared object failed to resolve.
cudaErrorSharedObjectInitFailed
This indicates that initialization of a shared object failed.
cudaErrorUnsupportedLimit
This indicates that the cudaLimit passed to the API call is not supported by the
active device.
cudaErrorDuplicateVariableName
This indicates that multiple global or constant variables (across separate CUDA
source files in the application) share the same string name.
cudaErrorDuplicateTextureName
This indicates that multiple textures (across separate CUDA source files in the
application) share the same string name.
cudaErrorDuplicateSurfaceName
This indicates that multiple surfaces (across separate CUDA source files in the
application) share the same string name.
cudaErrorDevicesUnavailable
This indicates that all CUDA devices are busy or unavailable at the current time.
Devices are often busy/unavailable due to use of cudaComputeModeExclusive,
cudaComputeModeProhibited or when long running CUDA kernels have filled up the GPU
and are blocking new work from starting. They can also be unavailable due to memory
constraints on a device that already has active CUDA work being performed.
cudaErrorInvalidKernelImage
This indicates that the device kernel image is invalid.
cudaErrorNoKernelImageForDevice
This indicates that there is no kernel image available that is suitable for the
device. This can occur when a user specifies code generation options for a
particular CUDA source file that do not include the corresponding device
configuration.
cudaErrorIncompatibleDriverContext
This indicates that the current context is not compatible with this the CUDA
Runtime. This can only occur if you are using CUDA Runtime/Driver interoperability
and have created an existing Driver context using the driver API. The Driver
context may be incompatible either because the Driver context was created using an
older version of the API, because the Runtime API call expects a primary driver
context and the Driver context is not primary, or because the Driver context has
been destroyed. Please see Interactions with the CUDA Driver API' for more
information.
cudaErrorPeerAccessAlreadyEnabled
This error indicates that a call to cudaDeviceEnablePeerAccess() is trying to re-
enable peer addressing on from a context which has already had peer addressing
enabled.
cudaErrorPeerAccessNotEnabled
This error indicates that cudaDeviceDisablePeerAccess() is trying to disable peer
addressing which has not been enabled yet via cudaDeviceEnablePeerAccess().
cudaErrorDeviceAlreadyInUse
This indicates that a call tried to access an exclusive-thread device that is
already in use by a different thread.
cudaErrorProfilerDisabled
This indicates profiler is not initialized for this run. This can happen when the
application is running with external profiling tools like visual profiler.
cudaErrorProfilerNotInitialized
Deprecated
This error return is deprecated as of CUDA 5.0. It is no longer an error to attempt to
enable/disable the profiling via cudaProfilerStart or cudaProfilerStop without
initialization.
cudaErrorProfilerAlreadyStarted
Deprecated
This error return is deprecated as of CUDA 5.0. It is no longer an error to call
cudaProfilerStart() when profiling is already enabled.
cudaErrorProfilerAlreadyStopped
Deprecated
This error return is deprecated as of CUDA 5.0. It is no longer an error to call
cudaProfilerStop() when profiling is already disabled.
cudaErrorAssert
An assert triggered in device code during kernel execution. The device cannot be
used again until cudaThreadExit() is called. All existing allocations are invalid
and must be reconstructed if the program is to continue using CUDA.
cudaErrorTooManyPeers
This error indicates that the hardware resources required to enable peer access
have been exhausted for one or more of the devices passed to
cudaEnablePeerAccess().
cudaErrorHostMemoryAlreadyRegistered
This error indicates that the memory range passed to cudaHostRegister() has already
been registered.
cudaErrorHostMemoryNotRegistered
This error indicates that the pointer passed to cudaHostUnregister() does not
correspond to any currently registered memory region.
cudaErrorOperatingSystem
This error indicates that an OS call failed.
cudaErrorPeerAccessUnsupported
This error indicates that P2P access is not supported across the given devices.
cudaErrorLaunchMaxDepthExceeded
This error indicates that a device runtime grid launch did not occur because the
depth of the child grid would exceed the maximum supported number of nested grid
launches.
cudaErrorLaunchFileScopedTex
This error indicates that a grid launch did not occur because the kernel uses file-
scoped textures which are unsupported by the device runtime. Kernels launched via
the device runtime only support textures created with the Texture Object API's.
cudaErrorLaunchFileScopedSurf
This error indicates that a grid launch did not occur because the kernel uses file-
scoped surfaces which are unsupported by the device runtime. Kernels launched via
the device runtime only support surfaces created with the Surface Object API's.
cudaErrorSyncDepthExceeded
This error indicates that a call to cudaDeviceSynchronize made from the device
runtime failed because the call was made at grid depth greater than than either the
default (2 levels of grids) or user specified device limit
cudaLimitDevRuntimeSyncDepth. To be able to synchronize on launched grids at a
greater depth successfully, the maximum nested depth at which cudaDeviceSynchronize
will be called must be specified with the cudaLimitDevRuntimeSyncDepth limit to the
cudaDeviceSetLimit api before the host-side launch of a kernel using the device
runtime. Keep in mind that additional levels of sync depth require the runtime to
reserve large amounts of device memory that cannot be used for user allocations.
cudaErrorLaunchPendingCountExceeded
This error indicates that a device runtime grid launch failed because the launch
would exceed the limit cudaLimitDevRuntimePendingLaunchCount. For this launch to
proceed successfully, cudaDeviceSetLimit must be called to set the
cudaLimitDevRuntimePendingLaunchCount to be higher than the upper bound of
outstanding launches that can be issued to the device runtime. Keep in mind that
raising the limit of pending device runtime launches will require the runtime to
reserve device memory that cannot be used for user allocations.
cudaErrorNotPermitted
This error indicates the attempted operation is not permitted.
cudaErrorNotSupported
This error indicates the attempted operation is not supported on the current system
or device.
cudaErrorHardwareStackError
Device encountered an error in the call stack during kernel execution, possibly due
to stack corruption or exceeding the stack size limit. This leaves the process in
an inconsistent state and any further CUDA work will return the same error. To
continue using CUDA, the process must be terminated and relaunched.
cudaErrorIllegalInstruction
The device encountered an illegal instruction during kernel execution This leaves
the process in an inconsistent state and any further CUDA work will return the same
error. To continue using CUDA, the process must be terminated and relaunched.
cudaErrorMisalignedAddress
The device encountered a load or store instruction on a memory address which is not
aligned. This leaves the process in an inconsistent state and any further CUDA work
will return the same error. To continue using CUDA, the process must be terminated
and relaunched.
cudaErrorInvalidAddressSpace
While executing a kernel, the device encountered an instruction which can only
operate on memory locations in certain address spaces (global, shared, or local),
but was supplied a memory address not belonging to an allowed address space. This
leaves the process in an inconsistent state and any further CUDA work will return
the same error. To continue using CUDA, the process must be terminated and
relaunched.
cudaErrorInvalidPc
The device encountered an invalid program counter. This leaves the process in an
inconsistent state and any further CUDA work will return the same error. To
continue using CUDA, the process must be terminated and relaunched.
cudaErrorIllegalAddress
The device encountered a load or store instruction on an invalid memory address.
This leaves the process in an inconsistent state and any further CUDA work will
return the same error. To continue using CUDA, the process must be terminated and
relaunched.
cudaErrorInvalidPtx
A PTX compilation failed. The runtime may fall back to compiling PTX if an
application does not contain a suitable binary for the current device.
cudaErrorInvalidGraphicsContext
This indicates an error with the OpenGL or DirectX context.
cudaErrorNvlinkUncorrectable
This indicates that an uncorrectable NVLink error was detected during the
execution.
cudaErrorJitCompilerNotFound
This indicates that the PTX JIT compiler library was not found. The JIT Compiler
library is used for PTX compilation. The runtime may fall back to compiling PTX if
an application does not contain a suitable binary for the current device.
cudaErrorCooperativeLaunchTooLarge
This error indicates that the number of blocks launched per grid for a kernel that
was launched via either cudaLaunchCooperativeKernel or
cudaLaunchCooperativeKernelMultiDevice exceeds the maximum number of blocks as
allowed by cudaOccupancyMaxActiveBlocksPerMultiprocessor or
cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags times the number of
multiprocessors as specified by the device attribute
cudaDevAttrMultiProcessorCount.
cudaErrorStartupFailure
This indicates an internal startup failure in the CUDA runtime.
cudaErrorApiFailureBase
Any unhandled CUDA driver error is added to this value and returned via the
runtime. Production releases of CUDA should not return such errors.
Deprecated
This error return is deprecated as of CUDA 4.1.
enum cudaFuncAttribute
CUDA function attributes that can be set using cudaFuncSetAttribute
Enumerator:
cudaFuncAttributeMaxDynamicSharedMemorySize
Maximum dynamic shared memory size
cudaFuncAttributePreferredSharedMemoryCarveout
Preferred shared memory-L1 cache split ratio
enum cudaFuncCache
CUDA function cache configurations
Enumerator:
cudaFuncCachePreferNone
Default function cache configuration, no preference
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
enum cudaGraphicsCubeFace
CUDA graphics interop array indices for cube maps
Enumerator:
cudaGraphicsCubeFacePositiveX
Positive X face of cubemap
cudaGraphicsCubeFaceNegativeX
Negative X face of cubemap
cudaGraphicsCubeFacePositiveY
Positive Y face of cubemap
cudaGraphicsCubeFaceNegativeY
Negative Y face of cubemap
cudaGraphicsCubeFacePositiveZ
Positive Z face of cubemap
cudaGraphicsCubeFaceNegativeZ
Negative Z face of cubemap
enum cudaGraphicsMapFlags
CUDA graphics interop map flags
Enumerator:
cudaGraphicsMapFlagsNone
Default; Assume resource can be read/written
cudaGraphicsMapFlagsReadOnly
CUDA will not write to this resource
cudaGraphicsMapFlagsWriteDiscard
CUDA will only write to and will not read from this resource
enum cudaGraphicsRegisterFlags
CUDA graphics interop register flags
Enumerator:
cudaGraphicsRegisterFlagsNone
Default
cudaGraphicsRegisterFlagsReadOnly
CUDA will not write to this resource
cudaGraphicsRegisterFlagsWriteDiscard
CUDA will only write to and will not read from this resource
cudaGraphicsRegisterFlagsSurfaceLoadStore
CUDA will bind this resource to a surface reference
cudaGraphicsRegisterFlagsTextureGather
CUDA will perform texture gather operations on this resource
enum cudaLimit
CUDA Limits
Enumerator:
cudaLimitStackSize
GPU thread stack size
cudaLimitPrintfFifoSize
GPU printf/fprintf FIFO size
cudaLimitMallocHeapSize
GPU malloc heap size
cudaLimitDevRuntimeSyncDepth
GPU device runtime synchronize depth
cudaLimitDevRuntimePendingLaunchCount
GPU device runtime pending launch count
enum cudaMemcpyKind
CUDA memory copy types
Enumerator:
cudaMemcpyHostToHost
Host -> Host
cudaMemcpyHostToDevice
Host -> Device
cudaMemcpyDeviceToHost
Device -> Host
cudaMemcpyDeviceToDevice
Device -> Device
cudaMemcpyDefault
Direction of the transfer is inferred from the pointer values. Requires unified
virtual addressing
enum cudaMemoryAdvise
CUDA Memory Advise values
Enumerator:
cudaMemAdviseSetReadMostly
Data will mostly be read and only occasionally be written to
cudaMemAdviseUnsetReadMostly
Undo the effect of cudaMemAdviseSetReadMostly
cudaMemAdviseSetPreferredLocation
Set the preferred location for the data as the specified device
cudaMemAdviseUnsetPreferredLocation
Clear the preferred location for the data
cudaMemAdviseSetAccessedBy
Data will be accessed by the specified device, so prevent page faults as much as
possible
cudaMemAdviseUnsetAccessedBy
Let the Unified Memory subsystem decide on the page faulting policy for the
specified device
enum cudaMemoryType
CUDA memory types
Enumerator:
cudaMemoryTypeHost
Host memory
cudaMemoryTypeDevice
Device memory
enum cudaMemRangeAttribute
CUDA range attributes
Enumerator:
cudaMemRangeAttributeReadMostly
Whether the range will mostly be read and only occasionally be written to
cudaMemRangeAttributePreferredLocation
The preferred location of the range
cudaMemRangeAttributeAccessedBy
Memory range has cudaMemAdviseSetAccessedBy set for specified device
cudaMemRangeAttributeLastPrefetchLocation
The last location to which the range was prefetched
enum cudaOutputMode
CUDA Profiler Output modes
Enumerator:
cudaKeyValuePair
Output mode Key-Value pair format.
cudaCSV
Output mode Comma separated values format.
enum cudaResourceType
CUDA resource types
Enumerator:
cudaResourceTypeArray
Array resource
cudaResourceTypeMipmappedArray
Mipmapped array resource
cudaResourceTypeLinear
Linear resource
cudaResourceTypePitch2D
Pitch 2D resource
enum cudaResourceViewFormat
CUDA texture resource view formats
Enumerator:
cudaResViewFormatNone
No resource view format (use underlying resource format)
cudaResViewFormatUnsignedChar1
1 channel unsigned 8-bit integers
cudaResViewFormatUnsignedChar2
2 channel unsigned 8-bit integers
cudaResViewFormatUnsignedChar4
4 channel unsigned 8-bit integers
cudaResViewFormatSignedChar1
1 channel signed 8-bit integers
cudaResViewFormatSignedChar2
2 channel signed 8-bit integers
cudaResViewFormatSignedChar4
4 channel signed 8-bit integers
cudaResViewFormatUnsignedShort1
1 channel unsigned 16-bit integers
cudaResViewFormatUnsignedShort2
2 channel unsigned 16-bit integers
cudaResViewFormatUnsignedShort4
4 channel unsigned 16-bit integers
cudaResViewFormatSignedShort1
1 channel signed 16-bit integers
cudaResViewFormatSignedShort2
2 channel signed 16-bit integers
cudaResViewFormatSignedShort4
4 channel signed 16-bit integers
cudaResViewFormatUnsignedInt1
1 channel unsigned 32-bit integers
cudaResViewFormatUnsignedInt2
2 channel unsigned 32-bit integers
cudaResViewFormatUnsignedInt4
4 channel unsigned 32-bit integers
cudaResViewFormatSignedInt1
1 channel signed 32-bit integers
cudaResViewFormatSignedInt2
2 channel signed 32-bit integers
cudaResViewFormatSignedInt4
4 channel signed 32-bit integers
cudaResViewFormatHalf1
1 channel 16-bit floating point
cudaResViewFormatHalf2
2 channel 16-bit floating point
cudaResViewFormatHalf4
4 channel 16-bit floating point
cudaResViewFormatFloat1
1 channel 32-bit floating point
cudaResViewFormatFloat2
2 channel 32-bit floating point
cudaResViewFormatFloat4
4 channel 32-bit floating point
cudaResViewFormatUnsignedBlockCompressed1
Block compressed 1
cudaResViewFormatUnsignedBlockCompressed2
Block compressed 2
cudaResViewFormatUnsignedBlockCompressed3
Block compressed 3
cudaResViewFormatUnsignedBlockCompressed4
Block compressed 4 unsigned
cudaResViewFormatSignedBlockCompressed4
Block compressed 4 signed
cudaResViewFormatUnsignedBlockCompressed5
Block compressed 5 unsigned
cudaResViewFormatSignedBlockCompressed5
Block compressed 5 signed
cudaResViewFormatUnsignedBlockCompressed6H
Block compressed 6 unsigned half-float
cudaResViewFormatSignedBlockCompressed6H
Block compressed 6 signed half-float
cudaResViewFormatUnsignedBlockCompressed7
Block compressed 7
enum cudaSharedCarveout
Shared memory carveout configurations
enum cudaSharedMemConfig
CUDA shared memory configuration
enum cudaSurfaceBoundaryMode
CUDA Surface boundary modes
Enumerator:
cudaBoundaryModeZero
Zero boundary mode
cudaBoundaryModeClamp
Clamp boundary mode
cudaBoundaryModeTrap
Trap boundary mode
enum cudaSurfaceFormatMode
CUDA Surface format modes
Enumerator:
cudaFormatModeForced
Forced format mode
cudaFormatModeAuto
Auto format mode
enum cudaTextureAddressMode
CUDA texture address modes
Enumerator:
cudaAddressModeWrap
Wrapping address mode
cudaAddressModeClamp
Clamp to edge address mode
cudaAddressModeMirror
Mirror address mode
cudaAddressModeBorder
Border address mode
enum cudaTextureFilterMode
CUDA texture filter modes
Enumerator:
cudaFilterModePoint
Point filter mode
cudaFilterModeLinear
Linear filter mode
enum cudaTextureReadMode
CUDA texture read modes
Enumerator:
cudaReadModeElementType
Read texture as specified element type
cudaReadModeNormalizedFloat
Read texture as normalized float
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