Class List
Here are the classes, structs, unions and interfaces with brief descriptions:

cutlass |
arch |
Mma | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, complex< double >, LayoutA, complex< double >, LayoutB, complex< double >, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, complex< double >, LayoutA, double, LayoutB, complex< double >, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, complex< float >, LayoutA, complex< float >, LayoutB, complex< float >, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, complex< float >, LayoutA, float, LayoutB, complex< float >, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, double, LayoutA, complex< double >, LayoutB, complex< double >, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, double, LayoutA, double, LayoutB, double, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, Operator > | Matrix multiply-add operation - specialized for 1x1x1x1 matrix multiply operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, float, LayoutA, complex< float >, LayoutB, complex< float >, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, float, LayoutA, float, LayoutB, float, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, half_t, LayoutA, half_t, LayoutB, float, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 1 >, 1, int, LayoutA, int, LayoutB, int, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 2 >, 1, int16_t, layout::RowMajor, int16_t, layout::ColumnMajor, int, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 1, 4 >, 1, int8_t, LayoutA, int8_t, LayoutB, int, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 1, 2, 1 >, 1, half_t, LayoutA, half_t, LayoutB, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 16, 16, 4 >, 32, half_t, LayoutA, half_t, LayoutB, ElementC, LayoutC, Operator > | Matrix multiply-add operation specialized for the entire warp
Mma< gemm::GemmShape< 16, 8, 8 >, 32, half_t, layout::RowMajor, half_t, layout::ColumnMajor, float, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F32 = F16 * F16 + F32
Mma< gemm::GemmShape< 16, 8, 8 >, 32, half_t, layout::RowMajor, half_t, layout::ColumnMajor, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation - F16 = F16 * F16 + F16
Mma< gemm::GemmShape< 2, 1, 1 >, 1, half_t, LayoutA, half_t, LayoutB, half_t, LayoutC, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 2, 2, 1 >, 1, half_t, layout::ColumnMajor, half_t, layout::RowMajor, half_t, layout::ColumnMajor, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 2, 2, 1 >, 1, half_t, layout::ColumnMajor, half_t, layout::RowMajor, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation
Mma< gemm::GemmShape< 8, 8, 128 >, 32, uint1b_t, layout::RowMajor, uint1b_t, layout::ColumnMajor, int, layout::RowMajor, OpXorPopc > | Matrix multiply-add operation
Mma< gemm::GemmShape< 8, 8, 16 >, 32, int8_t, layout::RowMajor, int8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = S8 * S8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, int8_t, layout::RowMajor, int8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = S8 * S8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, int8_t, layout::RowMajor, uint8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = S8 * U8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, int8_t, layout::RowMajor, uint8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = S8 * U8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, uint8_t, layout::RowMajor, int8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = U8 * S8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, uint8_t, layout::RowMajor, int8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = U8 * S8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, uint8_t, layout::RowMajor, uint8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = S8 * U8 + S32
Mma< gemm::GemmShape< 8, 8, 16 >, 32, uint8_t, layout::RowMajor, uint8_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = S8 * U8 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, int4b_t, layout::RowMajor, int4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = S4 * S4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, int4b_t, layout::RowMajor, int4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = S4 * S4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, int4b_t, layout::RowMajor, uint4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = S4 * U4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, int4b_t, layout::RowMajor, uint4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = S4 * U4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, uint4b_t, layout::RowMajor, int4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = U4 * S4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, uint4b_t, layout::RowMajor, int4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = U4 * S4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, uint4b_t, layout::RowMajor, uint4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: S32 = U4 * U4 + S32
Mma< gemm::GemmShape< 8, 8, 32 >, 32, uint4b_t, layout::RowMajor, uint4b_t, layout::ColumnMajor, int, layout::RowMajor, OpMultiplyAddSaturate > | Matrix multiply-add operation: S32 = U4 * U4 + S32
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::ColumnMajor, half_t, layout::ColumnMajor, float, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F32 = F16 * F16 + F32
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::ColumnMajor, half_t, layout::ColumnMajor, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F16 = F16 * F16 + F16
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::ColumnMajor, half_t, layout::RowMajor, float, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F32 = F16 * F16 + F32
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::ColumnMajor, half_t, layout::RowMajor, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F16 = F16 * F16 + F16
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::RowMajor, half_t, layout::ColumnMajor, float, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F32 = F16 * F16 + F32
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::RowMajor, half_t, layout::ColumnMajor, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F16 = F16 * F16 + F16
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::RowMajor, half_t, layout::RowMajor, float, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F32 = F16 * F16 + F32
Mma< gemm::GemmShape< 8, 8, 4 >, 8, half_t, layout::RowMajor, half_t, layout::RowMajor, half_t, layout::RowMajor, OpMultiplyAdd > | Matrix multiply-add operation: F16 = F16 * F16 + F16
PtxWmma | WMMA Matrix multiply-add operation
PtxWmmaLoadA | WMMA PTX string load for A, B, and C matrices
PtxWmmaLoadB |
PtxWmmaLoadC |
PtxWmmaStoreD | WMMA store for matrix D
Sm50 |
Sm60 |
Sm61 |
Sm70 |
Sm72 |
Sm75 |
Wmma< Shape_, cutlass::half_t, LayoutA_, cutlass::half_t, LayoutB_, ElementC_, LayoutC_, cutlass::arch::OpMultiplyAdd > |
Wmma< Shape_, cutlass::int4b_t, LayoutA_, cutlass::int4b_t, LayoutB_, int32_t, LayoutC_, cutlass::arch::OpMultiplyAdd > |
Wmma< Shape_, cutlass::uint1b_t, LayoutA_, cutlass::uint1b_t, LayoutB_, int32_t, LayoutC_, cutlass::arch::OpXorPopc > |
Wmma< Shape_, int8_t, LayoutA_, int8_t, LayoutB_, int32_t, LayoutC_, cutlass::arch::OpMultiplyAdd > |
Wmma< Shape_, uint8_t, LayoutA_, uint8_t, LayoutB_, int32_t, LayoutC_, cutlass::arch::OpMultiplyAdd > |
device_memory |
allocation | Device allocation abstraction that tracks size and capacity
deleter | Delete functor for CUDA device memory
epilogue |
thread |
Convert |
Params | Host-constructable parameters structure
LinearCombination |
Params | Host-constructable parameters structure
LinearCombinationClamp |
Params | Host-constructable parameters structure
LinearCombinationRelu |
Params | Host-constructable parameters structure
LinearCombinationRelu< ElementOutput_, Count, int, float, Round > |
Params | Host-constructable parameters structure
ReductionOpPlus |
Params | Host-constructable parameters structure
threadblock |
detail |
RowArrangement | RowArrangement determines how one or more warps cover a region of consecutive rows
RowArrangement< Shape, WarpsRemaining, ElementsPerAccess, ElementSize, false > | RowArrangement in which each warp's access is a 1D tiled arrangement
RowArrangement< Shape, WarpsRemaining, ElementsPerAccess, ElementSize, true > | RowArrangement in which each warp's access is a 2D tiled arrangement
Detail |
DefaultEpilogueComplexTensorOp | Defines sensible defaults for epilogues for TensorOps
DefaultEpilogueSimt | Defines sensible defaults for epilogues for SimtOps
DefaultEpilogueTensorOp | Defines sensible defaults for epilogues for TensorOps
DefaultEpilogueVoltaTensorOp | Defines sensible defaults for epilogues for TensorOps
DefaultEpilogueWmmaTensorOp | Defines sensible defaults for epilogues for WMMA TensorOps
DefaultInterleavedEpilogueTensorOp |
DefaultInterleavedThreadMapTensorOp | Defines the optimal thread map for TensorOp accumulator layouts
Detail |
DefaultThreadMapSimt | Defines the optimal thread map for SIMT accumulator layouts
Detail |
DefaultThreadMapTensorOp | Defines the optimal thread map for TensorOp accumulator layouts
Detail |
DefaultThreadMapVoltaTensorOp | Defines the optimal thread map for TensorOp accumulator layouts
DefaultThreadMapVoltaTensorOp< ThreadblockShape_, WarpShape_, PartitionsK, ElementOutput_, ElementsPerAccess, float > | Defines the optimal thread map for TensorOp accumulator layouts
Detail |
DefaultThreadMapVoltaTensorOp< ThreadblockShape_, WarpShape_, PartitionsK, ElementOutput_, ElementsPerAccess, half_t > | Defines the optimal thread map for TensorOp accumulator layouts
Detail |
DefaultThreadMapWmmaTensorOp | Defines the optimal thread map for Wmma TensorOp accumulator layouts
Detail |
DirectEpilogueTensorOp | Epilogue operator
Params | Parameters structure for host-constructible state
SharedStorage | Shared storage allocation needed by the epilogue
Epilogue | Epilogue operator without splitk
EpilogueBase | Base class for epilogues defining warp-level
SharedStorage | Shared storage allocation needed by the epilogue
InterleavedEpilogue | Epilogue operator without splitk
SharedStorage | Shared storage allocation needed by the epilogue
InterleavedOutputTileThreadMap |
Detail |
InterleavedPredicatedTileIterator |
Mask | Mask object
Params |
OutputTileOptimalThreadMap |
CompactedThreadMap | Compacted thread map in which the 4D region is contiguous
Detail |
OutputTileShape | Tuple defining point in output tile
OutputTileThreadMap |
PredicatedTileIterator |
Mask | Mask object
Params |
SharedLoadIterator |
warp |
FragmentIteratorComplexTensorOp |
FragmentIteratorComplexTensorOp< WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor > | Partial specialization for row-major shared memory
FragmentIteratorSimt | Fragment iterator for SIMT accumulator arrangements
FragmentIteratorSimt< WarpShape_, Operator_, layout::RowMajor, MmaSimtPolicy_ > | Partial specialization for row-major shared memory
FragmentIteratorTensorOp |
FragmentIteratorTensorOp< WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::ColumnMajorInterleaved< InterleavedK > > | Dedicated to interleaved layout
FragmentIteratorTensorOp< WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor > | Partial specialization for row-major shared memory
FragmentIteratorVoltaTensorOp |
FragmentIteratorVoltaTensorOp< WarpShape_, gemm::GemmShape< 32, 32, 4 >, float, layout::RowMajor > | Partial specialization for row-major shared memory
FragmentIteratorVoltaTensorOp< WarpShape_, gemm::GemmShape< 32, 32, 4 >, half_t, layout::RowMajor > | Partial specialization for row-major shared memory
FragmentIteratorWmmaTensorOp |
FragmentIteratorWmmaTensorOp< WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor > | Partial specialization for row-major shared memory
SimtPolicy |
SimtPolicy< WarpShape_, Operator_, layout::RowMajor, MmaSimtPolicy_ > | Partial specialization for row-major
TensorOpPolicy | Policy details related to the epilogue
TensorOpPolicy< WarpShape, OperatorShape, layout::ColumnMajorInterleaved< InterleavedK > > | Partial specialization for column-major-interleaved
TensorOpPolicy< WarpShape, OperatorShape, layout::RowMajor > | Partial specialization for row-major
TileIteratorSimt | Template for reading and writing tiles of accumulators to shared memory
TileIteratorSimt< WarpShape_, Operator_, Element_, layout::RowMajor, MmaSimtPolicy_ > | Template for reading and writing tiles of accumulators to shared memory
TileIteratorTensorOp | Template for reading and writing tiles of accumulators to shared memory
TileIteratorTensorOp< WarpShape_, OperatorShape_, Element_, layout::RowMajor > | Template for reading and writing tiles of accumulators to shared memory
Detail |
TileIteratorVoltaTensorOp | Template for reading and writing tiles of accumulators to shared memory
TileIteratorVoltaTensorOp< WarpShape_, gemm::GemmShape< 32, 32, 4 >, float, layout::RowMajor > | Template for reading and writing tiles of accumulators to shared memory
Detail |
TileIteratorVoltaTensorOp< WarpShape_, gemm::GemmShape< 32, 32, 4 >, half_t, layout::RowMajor > | Template for reading and writing tiles of accumulators to shared memory
Detail |
TileIteratorWmmaTensorOp | Template for reading and writing tiles of accumulators to shared memory
TileIteratorWmmaTensorOp< WarpShape_, OperatorShape_, OperatorFragment_, layout::RowMajor > | Template for reading and writing tiles of accumulators to shared memory
VoltaTensorOpPolicy | Policy details related to the epilogue
VoltaTensorOpPolicy< WarpShape_, gemm::GemmShape< 32, 32, 4 >, float, layout::RowMajor > | Partial specialization for row-major
VoltaTensorOpPolicy< WarpShape_, gemm::GemmShape< 32, 32, 4 >, half_t, layout::RowMajor > | Partial specialization for row-major
EpilogueWorkspace |
Params | Parameters structure
SharedStorage | Shared storage allocation needed by the epilogue
gemm |
device |
DefaultGemmConfiguration |
DefaultGemmConfiguration< arch::OpClassSimt, ArchTag, ElementA, ElementB, ElementC, ElementAccumulator > |
DefaultGemmConfiguration< arch::OpClassSimt, ArchTag, int8_t, int8_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm70, ElementA, ElementB, ElementC, ElementAccumulator > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, ElementA, ElementB, ElementC, ElementAccumulator > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, int4b_t, int4b_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, int4b_t, uint4b_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, int8_t, int8_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, int8_t, uint8_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, uint4b_t, int4b_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, uint4b_t, uint4b_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, uint8_t, int8_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassTensorOp, arch::Sm75, uint8_t, uint8_t, ElementC, int32_t > |
DefaultGemmConfiguration< arch::OpClassWmmaTensorOp, ArchTag, ElementA, ElementB, ElementC, ElementAccumulator > |
Gemm |
Arguments | Argument structure
Gemm< ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, layout::ColumnMajor, ElementAccumulator_, OperatorClass_, ArchTag_, ThreadblockShape_, WarpShape_, InstructionShape_, EpilogueOutputOp_, ThreadblockSwizzle_, Stages, AlignmentA, AlignmentB, SplitKSerial, Operator_, IsBetaZero > | Partial specialization for column-major output exchanges problem size and operand
Arguments | Argument structure
GemmBatched |
Arguments | Argument structure
GemmBatched< ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, layout::ColumnMajor, ElementAccumulator_, OperatorClass_, ArchTag_, ThreadblockShape_, WarpShape_, InstructionShape_, EpilogueOutputOp_, ThreadblockSwizzle_, Stages, AlignmentA, AlignmentB, Operator_ > | Partial specialization for column-major output exchanges problem size and operand
Arguments | Argument structure
GemmComplex |
Arguments | Argument structure
GemmComplex< ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, layout::ColumnMajor, ElementAccumulator_, OperatorClass_, ArchTag_, ThreadblockShape_, WarpShape_, InstructionShape_, EpilogueOutputOp_, ThreadblockSwizzle_, Stages, TransformA, TransformB, SplitKSerial > | Partial specialization for column-major output exchanges problem size and operand
Arguments | Argument structure
GemmSplitKParallel |
Arguments | Argument structure
GemmSplitKParallel< ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, layout::ColumnMajor, ElementAccumulator_, OperatorClass_, ArchTag_, ThreadblockShape_, WarpShape_, InstructionShape_, EpilogueOutputOp_, ConvertScaledOp_, ReductionOp_, ThreadblockSwizzle_, Stages, kAlignmentA, kAlignmentB, Operator_ > | Partial specialization for column-major output
Arguments | Argument structure
kernel |
detail |
GemvBatchedStridedEpilogueScaling |
DefaultGemm |

DefaultGemm< ElementA, layout::ColumnMajorInterleaved< InterleavedK >, kAlignmentA, ElementB, layout::RowMajorInterleaved< InterleavedK >, kAlignmentB, ElementC, layout::ColumnMajorInterleaved< InterleavedK >, int32_t, arch::OpClassTensorOp, arch::Sm75, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator, IsBetaZero >

Partial specialization for Turing Integer Matrix Multiply Interleaved layout

DefaultGemm< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC, layout::RowMajor, ElementAccumulator, arch::OpClassSimt, ArchTag, ThreadblockShape, WarpShape, GemmShape< 1, 1, 1 >, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator > | Partial specialization for SIMT
DefaultGemm< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC, layout::RowMajor, ElementAccumulator, arch::OpClassTensorOp, arch::Sm70, ThreadblockShape, WarpShape, GemmShape< 8, 8, 4 >, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator > | Partial specialization for Volta architecture
DefaultGemm< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC, layout::RowMajor, ElementAccumulator, arch::OpClassTensorOp, arch::Sm75, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator > | Partial specialization for Turing Architecture
DefaultGemm< int8_t, LayoutA, kAlignmentA, int8_t, LayoutB, kAlignmentB, ElementC, LayoutC, ElementAccumulator, arch::OpClassSimt, ArchTag, ThreadblockShape, WarpShape, GemmShape< 1, 1, 4 >, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator, false > | Partial specialization for SIMT DP4A
DefaultGemmSplitKParallel |
DefaultGemv |
Gemm |
Params | Parameters structure
SharedStorage | Shared memory storage structure
GemmBatched |
Params | Parameters structure
SharedStorage | Shared memory storage structure
GemmSplitKParallel |
Params | Parameters structure
SharedStorage | Shared memory storage structure
thread |
detail |
EnableMma_Crow_SM60 | Determines whether to enable thread::Gemm<> specializations compatible with SM50
Mma_HFMA2 | Structure to compute the matrix product for HFMA
Mma_HFMA2< Shape, layout::ColumnMajor, layout::ColumnMajor, layout::ColumnMajor, true > |
Mma_HFMA2< Shape, layout::ColumnMajor, layout::ColumnMajor, layout::RowMajor, true > |
Mma_HFMA2< Shape, layout::ColumnMajor, layout::RowMajor, layout::ColumnMajor, true > |
Mma_HFMA2< Shape, layout::ColumnMajor, layout::RowMajor, layout::RowMajor, true > |
Mma_HFMA2< Shape, layout::RowMajor, layout::ColumnMajor, layout::ColumnMajor, true > |
Mma_HFMA2< Shape, layout::RowMajor, layout::ColumnMajor, layout::RowMajor, true > |
Mma_HFMA2< Shape, layout::RowMajor, layout::RowMajor, layout::ColumnMajor, true > |
Mma_HFMA2< Shape, layout::RowMajor, layout::RowMajor, layout::RowMajor, true > |
Mma_HFMA2< Shape, LayoutA, LayoutB, layout::ColumnMajor, false > |
Mma_HFMA2< Shape, LayoutA, LayoutB, layout::RowMajor, false > |
Mma | Structure to compute the matrix product
Mma< Shape_, ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_, LayoutC_, arch::OpMultiplyAdd, bool > | Gemplate that handles conventional layouts for FFMA and DFMA GEMM
Mma< Shape_, half_t, LayoutA, half_t, LayoutB, half_t, LayoutC, arch::OpMultiplyAdd > | Structure to compute the matrix product
Mma< Shape_, half_t, LayoutA_, half_t, LayoutB_, half_t, layout::RowMajor, arch::OpMultiplyAdd, typename platform::enable_if< detail::EnableMma_Crow_SM60< LayoutA_, LayoutB_ >::value >::type > | Computes matrix product when C is row-major
Mma< Shape_, int8_t, layout::ColumnMajor, int8_t, layout::RowMajor, int32_t, LayoutC_, arch::OpMultiplyAdd, int8_t > | Gemplate that handles conventional layouts for IDP4A
Mma< Shape_, int8_t, layout::RowMajor, int8_t, layout::ColumnMajor, int32_t, LayoutC_, arch::OpMultiplyAdd, bool > | Gemplate that handles conventional layouts for IDP4A
MmaGeneric | Gemplate that handles all packed matrix layouts
threadblock |
DefaultGemvCore |
DefaultMma |
DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, layout::ColumnMajorInterleaved< InterleavedK >, OperatorClass, ArchTag, ThreadblockShape, WarpShape, InstructionShape, 2, Operator, true > | Specialization for column-major-interleaved output
DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, layout::RowMajor, arch::OpClassSimt, ArchTag, ThreadblockShape, WarpShape, InstructionShape, 2, Operator, false > | Specialization for row-major output (OperatorClass Simt)
DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, ArchTag, ThreadblockShape, WarpShape, InstructionShape, 2, Operator, false > | Specialization for row-major output (OperatorClass Simt)
DefaultMma< int8_t, LayoutA, kAlignmentA, int8_t, LayoutB, kAlignmentB, ElementAccumulator, layout::RowMajor, arch::OpClassSimt, ArchTag, ThreadblockShape, WarpShape, GemmShape< 1, 1, 4 >, 2, Operator, false > |
DefaultMmaCore |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 1 >, ElementA_, layout::ColumnMajor, ElementB_, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 1 >, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 1 >, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_, > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 1 >, ElementA_, layout::RowMajor, ElementB_, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 1 >, ElementA_, layout::RowMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 4 >, int8_t, layout::ColumnMajor, int8_t, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > | Partial specialization:
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 4 >, int8_t, layout::ColumnMajor, int8_t, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 4 >, int8_t, layout::RowMajor, int8_t, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > | Partial specialization:
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 1, 1, 4 >, int8_t, layout::RowMajor, int8_t, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassSimt, 2, Operator_ > | Partial specialization:
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 8, 8, 4 >, ElementA_, layout::ColumnMajor, ElementB_, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 8, 8, 4 >, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 8, 8, 4 >, ElementA_, layout::RowMajor, ElementB_, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, GemmShape< 8, 8, 4 >, ElementA_, layout::RowMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, InstructionShape_, ElementA_, layout::ColumnMajor, ElementB_, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, InstructionShape_, ElementA_, layout::ColumnMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, InstructionShape_, ElementA_, layout::ColumnMajorInterleaved< InterleavedK >, ElementB_, layout::RowMajorInterleaved< InterleavedK >, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_, AccumulatorsInRowMajor > |
DefaultMmaCore< Shape_, WarpShape_, InstructionShape_, ElementA_, layout::RowMajor, ElementB_, layout::ColumnMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
DefaultMmaCore< Shape_, WarpShape_, InstructionShape_, ElementA_, layout::RowMajor, ElementB_, layout::RowMajor, ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_ > |
GemmBatchedIdentityThreadblockSwizzle | Threadblock swizzling function for batched GEMMs
GemmHorizontalThreadblockSwizzle | Threadblock swizzling function for GEMMs
GemmIdentityThreadblockSwizzle | Threadblock swizzling function for GEMMs
GemmSplitKHorizontalThreadblockSwizzle | Threadblock swizzling function for split-K GEMMs
GemmSplitKIdentityThreadblockSwizzle | Threadblock swizzling function for split-K GEMMs
Gemv | Structure to compute the matrix-vector product using SIMT math instructions
GemvBatchedStridedThreadblockDefaultSwizzle | Threadblock swizzling function for batched GEMVs
MmaBase |
SharedStorage | Shared storage object needed by threadblock-scoped GEMM
MmaPipelined | Structure to compute the matrix product targeting CUDA cores and SIMT math instructions
MmaPolicy | Policy object describing MmaTensorOp
MmaSingleStage | Structure to compute the matrix product targeting CUDA cores and SIMT math instructions
warp |
DefaultMmaTensorOp | Partial specialization for m-by-n-by-kgroup
MmaComplexTensorOp |
MmaComplexTensorOp< Shape_, complex< RealElementA >, LayoutA_, complex< RealElementB >, LayoutB_, complex< RealElementC >, LayoutC_, Policy_, TransformA, TransformB, Enable > | Partial specialization for complex*complex+complex => complex using real-valued TensorOps
MmaSimt | Structure to compute the matrix product targeting CUDA cores and SIMT math instructions
MmaSimtPolicy | Describes the arrangement and configuration of per-lane operations in warp-level matrix multiply
MmaSimtTileIterator |
MmaSimtTileIterator< Shape_, Operand::kA, Element_, layout::ColumnMajor, Policy_, PartitionsK, PartitionGroupSize > |
MmaSimtTileIterator< Shape_, Operand::kA, Element_, layout::ColumnMajorInterleaved< 4 >, Policy_, PartitionsK, PartitionGroupSize > |
MmaSimtTileIterator< Shape_, Operand::kB, Element_, layout::RowMajor, Policy_, PartitionsK, PartitionGroupSize > |
MmaSimtTileIterator< Shape_, Operand::kB, Element_, layout::RowMajorInterleaved< 4 >, Policy_, PartitionsK, PartitionGroupSize > |
MmaSimtTileIterator< Shape_, Operand::kC, Element_, layout::ColumnMajor, Policy_ > |
MmaSimtTileIterator< Shape_, Operand::kC, Element_, layout::RowMajor, Policy_ > |
MmaTensorOp | Structure to compute the matrix product targeting CUDA cores and SIMT math instructions
MmaTensorOpAccumulatorTileIterator |
MmaTensorOpAccumulatorTileIterator< Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ > |
Policy | Internal structure of iterator - made public to enable introspection
MmaTensorOpAccumulatorTileIterator< Shape_, Element_, cutlass::layout::ColumnMajorInterleaved< InterleavedN >, InstructionShape_, OpDelta_ > |
Policy | Internal structure of iterator - made public to enable introspection
MmaTensorOpAccumulatorTileIterator< Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ > |
Policy | Internal structure of iterator - made public to enable introspection
MmaTensorOpMultiplicandTileIterator |
MmaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, InstructionShape_, OpDelta_, 32, PartitionsK_ > |
MmaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, InstructionShape_, OpDelta_, 32, PartitionsK_ > |
MmaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, InstructionShape_, OpDelta_, 32, PartitionsK_ > |
MmaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, InstructionShape_, OpDelta_, 32, PartitionsK_ > |
MmaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, 64 >, InstructionShape_, OpDelta_, 32, PartitionsK_ > |
Policy | Internal structure of iterator - made public to enable introspection
MmaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, InstructionShape_, OpDelta_, 32, PartitionsK_ > |
Policy | Internal structure of iterator - made public to enable introspection
MmaTensorOpPolicy | Policy
MmaVoltaTensorOp | Structure to compute the matrix product targeting CUDA cores and SIMT math instructions
MmaVoltaTensorOpAccumulatorTileIterator |
Policy | Internal structure of iterator - made public to enable introspection
MmaVoltaTensorOpMultiplicandTileIterator |
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand::kA, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value >, InstructionShape_, OpDelta_, 32 > |
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand::kA, Element_, cutlass::layout::VoltaTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value >, InstructionShape_, OpDelta_, 32 > |
Policy | Internal structure of iterator - made public to enable introspection
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand::kB, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous< sizeof_bits< Element_ >::value >, InstructionShape_, OpDelta_, 32 > |
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand::kB, Element_, cutlass::layout::VoltaTensorOpMultiplicandBCongruous< sizeof_bits< Element_ >::value >, InstructionShape_, OpDelta_, 32 > |
Policy | Internal structure of iterator - made public to enable introspection
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, KBlock >, InstructionShape_, OpDelta_, 32 > |
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::RowMajorVoltaTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, KBlock >, InstructionShape_, OpDelta_, 32 > |
MmaVoltaTensorOpMultiplicandTileIterator< Shape_, Operand_, Element_, cutlass::layout::VoltaTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, KBlock >, InstructionShape_, OpDelta_, 32 > |
Policy | Internal structure of iterator - made public to enable introspection
WarpSize | Query the number of threads per warp
BatchedGemmCoord |
GemmCoord |
GemmShape | Shape of a matrix multiply-add operation
layout |
ColumnMajor | Mapping function for column-major matrices
ColumnMajorBlockLinear |
ColumnMajorInterleaved |
ColumnMajorTensorOpMultiplicandCongruous |
ColumnMajorTensorOpMultiplicandCrosswise |
ColumnMajorVoltaTensorOpMultiplicandBCongruous | Template mapping a column-major view of pitch-linear memory to VoltaTensorOpMultiplicandCongruous
ColumnMajorVoltaTensorOpMultiplicandCongruous | Template mapping a column-major view of pitch-linear memory to VoltaTensorOpMultiplicandCongruous
ColumnMajorVoltaTensorOpMultiplicandCrosswise |
ContiguousMatrix |
GeneralMatrix |
LayoutTranspose | Defines transposes of matrix layouts
LayoutTranspose< layout::ColumnMajor > | Transpose of column-major is row-major
LayoutTranspose< layout::RowMajor > | Transpose of row-major is column-major
PackedVectorLayout | Tensor layout for densely packed vectors
PitchLinear | Mapping function for pitch-linear memory
PitchLinearCoord | Coordinate in pitch-linear space
PitchLinearShape | Template defining a shape used by pitch-linear operators
RowMajor | Mapping function for row-major matrices
RowMajorBlockLinear |
RowMajorInterleaved |
RowMajorTensorOpMultiplicandCongruous |
RowMajorTensorOpMultiplicandCrosswise |
RowMajorVoltaTensorOpMultiplicandBCongruous | Template mapping a row-major view of pitch-linear memory to VoltaTensorOpMultiplicandCongruous
RowMajorVoltaTensorOpMultiplicandCongruous | Template mapping a row-major view of pitch-linear memory to VoltaTensorOpMultiplicandCongruous
RowMajorVoltaTensorOpMultiplicandCrosswise |
TensorCxRSKx | Mapping function for 4-D CxRSKx tensors
TensorNCHW | Mapping function for 4-D NCHW tensors
TensorNCxHWx | Mapping function for 4-D NC/xHWx tensors
TensorNHWC | Mapping function for 4-D NHWC tensors
TensorOpMultiplicand |
TensorOpMultiplicandColumnMajorInterleaved | Template based on element size (in bits) - defined in terms of pitch-linear memory
TensorOpMultiplicandCongruous |
TensorOpMultiplicandCongruous< 32, Crosswise > |
TensorOpMultiplicandCrosswise |
TensorOpMultiplicandRowMajorInterleaved | Template based on element size (in bits) - defined in terms of pitch-linear memory
VoltaTensorOpMultiplicandBCongruous | Template based on element size (in bits) - defined in terms of pitch-linear memory
VoltaTensorOpMultiplicandCongruous | Template based on element size (in bits) - defined in terms of pitch-linear memory
VoltaTensorOpMultiplicandCrosswise |
library |
GemmArguments | Arguments for GEMM
GemmArrayArguments | Arguments for GEMM - used by all the GEMM operations
GemmArrayConfiguration | Configuration for batched GEMM in which multiple matrix products are computed
GemmBatchedConfiguration | Configuration for batched GEMM in which multiple matrix products are computed
GemmConfiguration | Configuration for basic GEMM operations
GemmDescription | Description of all GEMM computations
GemmPlanarComplexBatchedConfiguration | Batched complex valued GEMM in which real and imaginary parts are separated by a stride
GemmPlanarComplexConfiguration | Complex valued GEMM in which real and imaginary parts are separated by a stride
Manifest | Manifest of CUTLASS Library
MathInstructionDescription |
Operation | Base class for all device-wide operations
OperationDescription | High-level description of an operation
TensorDescription | Structure describing the properties of a tensor
TileDescription | Structure describing the tiled structure of a GEMM-like computation
platform |
aligned_chunk |
aligned_storage | Std::aligned_storage
alignment_of | Std::alignment_of
pad |
alignment_of< const value_t > |
alignment_of< const volatile value_t > |
alignment_of< double2 > |
alignment_of< double4 > |
alignment_of< float4 > |
alignment_of< int4 > |
alignment_of< long4 > |
alignment_of< longlong2 > |
alignment_of< longlong4 > |
alignment_of< uint4 > |
alignment_of< ulong4 > |
alignment_of< ulonglong2 > |
alignment_of< ulonglong4 > |
alignment_of< volatile value_t > |
bool_constant | Std::bool_constant
conditional | Std::conditional (true specialization)
conditional< false, T, F > | Std::conditional (false specialization)
default_delete | Default deleter
default_delete< T[]> | Partial specialization for deleting array types
enable_if | Std::enable_if (true specialization)
enable_if< false, T > | Std::enable_if (false specialization)
integral_constant | Std::integral_constant
is_arithmetic | Std::is_arithmetic
is_base_of | Std::is_base_of
is_base_of_helper | Helper for std::is_base_of
dummy |
is_floating_point | Std::is_floating_point
is_fundamental | Std::is_fundamental
is_integral | Std::is_integral
is_integral< char > |
is_integral< const T > |
is_integral< const volatile T > |
is_integral< int > |
is_integral< long > |
is_integral< long long > |
is_integral< short > |
is_integral< signed char > |
is_integral< unsigned char > |
is_integral< unsigned int > |
is_integral< unsigned long > |
is_integral< unsigned long long > |
is_integral< unsigned short > |
is_integral< volatile T > |
is_pointer | Std::is_pointer
is_pointer_helper | Helper for std::is_pointer (false specialization)
is_pointer_helper< T * > | Helper for std::is_pointer (true specialization)
is_same | Std::is_same (false specialization)
is_same< A, A > | Std::is_same (true specialization)
is_trivially_copyable |
is_void | Std::is_void
is_volatile | Std::is_volatile
is_volatile< volatile T > |
nullptr_t | Std::nullptr_t
remove_const | Std::remove_const (non-const specialization)
remove_const< const T > | Std::remove_const (const specialization)
remove_cv | Std::remove_cv
remove_volatile | Std::remove_volatile (non-volatile specialization)
remove_volatile< volatile T > | Std::remove_volatile (volatile specialization)
unique_ptr | Std::unique_ptr
reduction |
kernel |
ReduceSplitK |
Params | Params structure
SharedStorage |
thread |
Reduce | Structure to compute the thread level reduction
Reduce< plus< half_t >, AlignedArray< half_t, N > > | Partial specializations of Reduce for AlignedArray<half_t, N>
Reduce< plus< half_t >, Array< half_t, N > > | Partial specializations of Reduce for Array<half_t, N>
Reduce< plus< T >, Array< T, N > > | Partial specialization of Reduce for Array<T, N>
Reduce< plus< T >, T > | Partial Specialization of Reduce for "plus" (a functional operator)
ReduceAdd | Mixed-precision reduction
Params |
BatchedReduction |
BatchedReductionTraits |
Params |
DefaultBlockSwizzle |
reference |
detail |
Cast |
Cast< float, int8_t > |
Cast< float, uint8_t > |
device |
detail |
RandomGaussianFunc |
Params | Parameters structure
RandomUniformFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorCopyDiagonalInFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorCopyDiagonalOutFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorFillDiagonalFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorFillLinearFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorFillRandomGaussianFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorFillRandomUniformFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorUpdateDiagonalFunc | Computes a random Gaussian distribution
Params | Parameters structure
TensorUpdateOffDiagonalFunc | Computes a random Gaussian distribution
Params | Parameters structure
kernel |
detail | Defines several helpers
TensorForEachHelper | Helper to perform for-each operation
TensorForEachHelper< Func, Rank, 0 > | Helper to perform for-each operation
thread |
Gemm | Thread-level blocked general matrix product
BlockForEach |
Gemm |
Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, AccumulatorType, arch::OpMultiplyAdd > | Partial specialization for multiply-add
Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, AccumulatorType, arch::OpMultiplyAddSaturate > | Partial specialization for multiply-add-saturate
Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, AccumulatorType, arch::OpXorPopc > | Partial specialization for XOR-popc
TensorDiagonalForEach | Launches a kernel calling a functor for each element along a tensor's diagonal
TensorForEach | Launches a kernel calling a functor for each element in a tensor's index space
host |
detail | Defines several helpers
RandomGaussianFunc |
RandomGaussianFunc< complex< Element > > | Partial specialization for initializing a complex value
RandomUniformFunc |
RandomUniformFunc< complex< Element > > | Partial specialization for initializing a complex value
TensorContainsFunc | < Layout function
TensorCopyIf | Helper to conditionally copy between tensor views
TensorEqualsFunc | < Layout function
TensorFillDiagonalFunc | < Layout function
TensorFillFunc | < Layout function
TensorFillGaussianFunc | Computes a random Gaussian distribution
TensorFillLinearFunc | < Layout function
TensorFillRandomUniformFunc | Computes a random Gaussian distribution
TensorForEachHelper | Helper to perform for-each operation
TensorForEachHelper< Func, Rank, 0 > | Helper to perform for-each operation
TensorFuncBinaryOp | Helper to apply a binary operator in place
TensorUpdateOffDiagonalFunc | < Layout function
TrivialConvert | Helper to convert between types
BlockForEach |
Gemm |
Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, ComputeType, arch::OpMultiplyAdd > | Partial specialization for multiply-add
Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, ComputeType, arch::OpMultiplyAddSaturate > | Partial specialization for multiply-add-saturate
Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, ComputeType, arch::OpXorPopc > | Partial specialization for XOR-popc
thread |
Matrix | Per-thread matrix object storing a packed matrix
transform |
thread |
Transpose | Transforms a fragment by doing a transpose
Transpose< ElementCount_, layout::PitchLinearShape< 4, 4 >, int8_t > | Specialization for int8_t 4x4 transpose
threadblock |
PredicatedTileAccessIterator |
PredicatedTileAccessIterator2dThreadTile |
PredicatedTileAccessIterator2dThreadTile< Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator2dThreadTile< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator2dThreadTile< Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator< Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator< Shape_, Element_, layout::ColumnMajorInterleaved< InterleavedK >, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator< Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileAccessIterator< Shape_, Element_, layout::RowMajorInterleaved< InterleavedK >, AdvanceRank, ThreadMap_, AccessType_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator |
PredicatedTileIterator2dThreadTile |
PredicatedTileIterator2dThreadTile< Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, Transpose_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator2dThreadTile< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Transpose_ > |
AccessType |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator2dThreadTile< Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, Transpose_ > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator< Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, AccessSize > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator< Shape_, Element_, layout::ColumnMajorInterleaved< InterleavedK >, AdvanceRank, ThreadMap_, AccessSize > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, AccessSize > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator< Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, AccessSize > |
Params | Parameters object is precomputed state and is host-constructible
PredicatedTileIterator< Shape_, Element_, layout::RowMajorInterleaved< InterleavedK >, AdvanceRank, ThreadMap_, AccessSize > |
Params | Parameters object is precomputed state and is host-constructible
RegularTileAccessIterator |
RegularTileAccessIterator< Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::ColumnMajorTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::ColumnMajorTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::RowMajorTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::RowMajorTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileAccessIterator< Shape_, Element_, layout::TensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
RegularTileAccessIterator< Shape_, Element_, layout::TensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
RegularTileIterator |
RegularTileIterator2dThreadTile |
RegularTileIterator2dThreadTile< Shape_, Element_, layout::ColumnMajorInterleaved< 4 >, AdvanceRank, ThreadMap_, Alignment > | Regular tile iterator specialized for interleaved layout + 2d thread-tiled threadmapping
RegularTileIterator2dThreadTile< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment > | Regular tile iterator specialized for pitch-linear + 2d thread-tiled threadmapping
RegularTileIterator2dThreadTile< Shape_, Element_, layout::RowMajorInterleaved< 4 >, AdvanceRank, ThreadMap_, Alignment > | Regular tile iterator specialized for interleaved layout + 2d thread-tiled threadmapping
RegularTileIterator< Shape_, Element_, layout::ColumnMajor, AdvanceRank, ThreadMap_, Alignment > | Regular tile iterator specialized for pitch-linear
RegularTileIterator< Shape_, Element_, layout::ColumnMajorTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::ColumnMajorTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandBCongruous< sizeof_bits< Element_ >::value >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Shape_::kRow >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment > | Regular tile iterator specialized for pitch-linear
RegularTileIterator< Shape_, Element_, layout::RowMajor, AdvanceRank, ThreadMap_, Alignment > | Regular tile iterator specialized for pitch-linear
RegularTileIterator< Shape_, Element_, layout::RowMajorTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::RowMajorTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandBCongruous< sizeof_bits< Element_ >::value >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::RowMajorVoltaTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Shape_::kColumn >, AdvanceRank, ThreadMap_, Alignment > |
RegularTileIterator< Shape_, Element_, layout::TensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value, int(128/sizeof(Element_))>, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
RegularTileIterator< Shape_, Element_, layout::TensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Crosswise >, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
RegularTileIterator< Shape_, Element_, layout::VoltaTensorOpMultiplicandBCongruous< sizeof_bits< Element_ >::value >, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
RegularTileIterator< Shape_, Element_, layout::VoltaTensorOpMultiplicandCongruous< sizeof_bits< Element_ >::value >, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
RegularTileIterator< Shape_, Element_, layout::VoltaTensorOpMultiplicandCrosswise< sizeof_bits< Element_ >::value, Shape_::kContiguous >, AdvanceRank, ThreadMap_, Alignment > |
Detail | Internal details made public to facilitate introspection
PitchLinear2DThreadTileStripminedThreadMap |
PitchLinear2DThreadTileStripminedThreadMap< Shape_, Threads, cutlass::layout::PitchLinearShape< 4, 4 > > |
Detail | Internal implementation details
PitchLinearStripminedThreadMap |
Detail | Internal implementation details
PitchLinearTilePolicyStripminedThreadContiguous |
PitchLinearTilePolicyStripminedThreadStrided |
PitchLinearWarpRakedThreadMap |
Detail | Internal details made public to facilitate introspection Iterations along each dimension (concept: PitchLinearShape)
PitchLinearWarpStripedThreadMap |
Detail | Internal details made public to facilitate introspection Iterations along each dimension (concept: PitchLinearShape)
TransposePitchLinearThreadMap |
Detail | Internal details made public to facilitate introspection Iterations along each dimension (concept: PitchLinearShape)
TransposePitchLinearThreadMap2DThreadTile | Thread Mapping a 2D threadtiled mapping as a transposed Pitchlinear2DThreadTile mapping
TransposePitchLinearThreadMapSimt |
AlignedArray | Aligned array type
AlignedBuffer | Modifies semantics of cutlass::Array<> to provide guaranteed alignment
Array< T, N, false > | Statically sized array for any data type
const_iterator | Bidirectional constant iterator over elements
const_reference | Reference object extracts sub-byte items
const_reverse_iterator | Bidirectional constant iterator over elements
iterator | Bidirectional iterator over elements
reference | Reference object inserts or extracts sub-byte items
reverse_iterator | Bidirectional iterator over elements
Array< T, N, true > | Statically sized array for any data type
const_iterator | Bidirectional constant iterator over elements
const_reverse_iterator | Bidirectional constant iterator over elements
iterator | Bidirectional iterator over elements
reverse_iterator | Bidirectional iterator over elements
CommandLine |
complex |
ConstSubbyteReference |
Coord | Statically-sized array specifying Coords within a tensor
cuda_exception | C++ exception wrapper for CUDA `cudaError_t`
Distribution | Distribution type
divide_assert |
divides |
divides< Array< half_t, N > > |
divides< Array< T, N > > |
FloatType | Defines a floating-point type based on the number of exponent and mantissa bits
FloatType< 11, 52 > |
FloatType< 5, 10 > |
FloatType< 8, 23 > |
half_t | IEEE half-precision floating-point type
HostTensor | Host tensor
IdentityTensorLayout |
integer_subbyte | 4-bit signed integer type
IntegerType | Defines integers based on size and whether they are signed
IntegerType< 1, false > |
IntegerType< 1, true > |
IntegerType< 16, false > |
IntegerType< 16, true > |
IntegerType< 32, false > |
IntegerType< 32, true > |
IntegerType< 4, false > |
IntegerType< 4, true > |
IntegerType< 64, false > |
IntegerType< 64, true > |
IntegerType< 8, false > |
IntegerType< 8, true > |
is_pow2 |
KernelLaunchConfiguration | Structure containing the basic launch configuration of a CUDA kernel
log2_down |
log2_down< N, 1, Count > |
log2_up |
log2_up< N, 1, Count > |
MatrixCoord |
MatrixShape | Describes the size of a matrix tile
Max |
maximum |
maximum< Array< T, N > > |
maximum< float > |
Min |
minimum |
minimum< Array< T, N > > |
minimum< float > |
minus |
minus< Array< half_t, N > > |
minus< Array< T, N > > |
multiplies |
multiplies< Array< half_t, N > > |
multiplies< Array< T, N > > |
multiply_add | Fused multiply-add
multiply_add< Array< half_t, N >, Array< half_t, N >, Array< half_t, N > > | Fused multiply-add
multiply_add< Array< T, N >, Array< T, N >, Array< T, N > > | Fused multiply-add
multiply_add< complex< T >, complex< T >, complex< T > > | Fused multiply-add
multiply_add< complex< T >, T, complex< T > > | Fused multiply-add
multiply_add< T, complex< T >, complex< T > > | Fused multiply-add
negate |
negate< Array< half_t, N > > |
negate< Array< T, N > > |
NumericArrayConverter | Conversion operator for Array
NumericArrayConverter< float, half_t, 2, Round > | Partial specialization for Array<float, 2> <= Array<half_t, 2>, round to nearest
NumericArrayConverter< float, half_t, N, Round > | Partial specialization for Array<half> <= Array<float>
NumericArrayConverter< half_t, float, 2, FloatRoundStyle::round_to_nearest > | Partial specialization for Array<half, 2> <= Array<float, 2>, round to nearest
NumericArrayConverter< half_t, float, N, Round > | Partial specialization for Array<half> <= Array<float>
NumericConverter |
NumericConverter< float, half_t, Round > | Partial specialization for float <= half_t
NumericConverter< half_t, float, FloatRoundStyle::round_to_nearest > | Specialization for round-to-nearest
NumericConverter< half_t, float, FloatRoundStyle::round_toward_zero > | Specialization for round-toward-zero
NumericConverter< int8_t, float, Round > |
NumericConverter< T, T, Round > | Partial specialization for float <= half_t
NumericConverterClamp |
plus |
plus< Array< half_t, N > > |
plus< Array< T, N > > |
PredicateVector | Statically sized array of bits implementing
ConstIterator | An iterator implementing Predicate Iterator Concept enabling sequential read and write access to predicates
Iterator | An iterator implementing Predicate Iterator Concept enabling sequential read and write access to predicates
TrivialIterator | Iterator that always returns true
RealType | Used to determine the real-valued underlying type of a numeric type T
RealType< complex< T > > | Partial specialization for complex-valued type
ReferenceFactory |
ReferenceFactory< Element, false > |
ReferenceFactory< Element, true > |
ScalarIO | Helper to enable formatted printing of CUTLASS scalar types to an ostream
Semaphore | CTA-wide semaphore for inter-CTA synchronization
sizeof_bits | Defines the size of an element in bits
sizeof_bits< Array< T, N, RegisterSized > > | Statically sized array for any data type
sizeof_bits< bin1_t > | Defines the size of an element in bits - specialized for bin1_t
sizeof_bits< int4b_t > | Defines the size of an element in bits - specialized for int4b_t
sizeof_bits< uint1b_t > | Defines the size of an element in bits - specialized for uint1b_t
sizeof_bits< uint4b_t > | Defines the size of an element in bits - specialized for uint4b_t
sqrt_est |
SubbyteReference |
Tensor4DCoord | Defines a canonical 4D coordinate used by tensor operations
TensorRef |
TensorView |
TypeTraits |
TypeTraits< complex< double > > |
integer_type |
unsigned_type |
TypeTraits< complex< float > > |
TypeTraits< complex< half > > |
TypeTraits< complex< half_t > > |
TypeTraits< double > |
TypeTraits< float > |
TypeTraits< half_t > |
TypeTraits< int > |
TypeTraits< int64_t > |
TypeTraits< int8_t > |
TypeTraits< uint64_t > |
TypeTraits< uint8_t > |
TypeTraits< unsigned > |
xor_add | Fused multiply-add
std | STL namespace
numeric_limits< cutlass::half_t > | Numeric limits
DebugType |
DebugValue |