cudaResViewFormatUnsignedInt2 (3)
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 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 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 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 }
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 }
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, cudaErrorStartupFailure = 0x7f, cudaErrorApiFailureBase = 10000 }
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 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 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 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
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.
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. 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.
- 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. The context cannot be used, so it must be destroyed (and a new one should be created). All existing device memory allocations from this context are invalid and must be reconstructed if the program is to continue using CUDA.
- cudaErrorIllegalInstruction
- The device encountered an illegal instruction during kernel execution The context cannot be used, so it must be destroyed (and a new one should be created). All existing device memory allocations from this context are invalid and must be reconstructed if the program is to continue using CUDA.
- cudaErrorMisalignedAddress
- The device encountered a load or store instruction on a memory address which is not aligned. The context cannot be used, so it must be destroyed (and a new one should be created). All existing device memory allocations from this context are invalid and must be reconstructed if the program is to continue using CUDA.
- 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. The context cannot be used, so it must be destroyed (and a new one should be created). All existing device memory allocations from this context are invalid and must be reconstructed if the program is to continue using CUDA.
- cudaErrorInvalidPc
- The device encountered an invalid program counter. The context cannot be used, so it must be destroyed (and a new one should be created). All existing device memory allocations from this context are invalid and must be reconstructed if the program is to continue using CUDA.
- cudaErrorIllegalAddress
- The device encountered a load or store instruction on an invalid memory address. The context cannot be used, so it must be destroyed (and a new one should be created). All existing device memory allocations from this context are invalid and must be reconstructed if the program is to continue using CUDA.
- 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.
- 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 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 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
Author
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