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IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ /*! \file \brief Default kernel-level GEMM definitions combine threadblock-scoped matrix multiply-add with the appropriate threadblock-scoped epilogue. Note, CUTLASS epilogues universally target row-major outputs. Column-major outputs are accommodated by exchanging A and B operands and assuming transposed layouts. Partial specializations here choose 'device::GemmTransposed' to implement this functionality. */ #pragma once #include "cutlass/cutlass.h" #include "cutlass/layout/matrix.h" #include "cutlass/numeric_types.h" #include "cutlass/arch/wmma.h" #include "cutlass/epilogue/threadblock/epilogue.h" #include "cutlass/epilogue/thread/linear_combination.h" #include "cutlass/gemm/gemm.h" #include "cutlass/gemm/kernel/gemm.h" #include "cutlass/gemm/kernel/gemm_pipelined.h" #include "cutlass/gemm/threadblock/default_mma_core_sm75.h" #include "cutlass/gemm/threadblock/default_mma_core_sm70.h" #include "cutlass/gemm/threadblock/default_mma_core_sm80.h" #include "cutlass/gemm/threadblock/default_mma.h" #include "cutlass/gemm/threadblock/default_mma_core_simt.h" #include "cutlass/gemm/threadblock/threadblock_swizzle.h" #include "cutlass/epilogue/threadblock/default_epilogue_tensor_op.h" #include "cutlass/epilogue/threadblock/default_epilogue_volta_tensor_op.h" #include "cutlass/epilogue/threadblock/default_epilogue_simt.h" #include "cutlass/transform/threadblock/predicated_tile_iterator.h" #include "cutlass/layout/permute.h" #if defined(CUTLASS_ARCH_WMMA_ENABLED) #include "cutlass/epilogue/threadblock/default_epilogue_wmma_tensor_op.h" #endif //CUTLASS_ARCH_WMMA_ENABLED //////////////////////////////////////////////////////////////////////////////// namespace cutlass { namespace gemm { namespace kernel { //////////////////////////////////////////////////////////////////////////////// template < /// Element type for A matrix operand typename ElementA_, /// Layout type for A matrix operand typename LayoutA_, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB_, /// Layout type for B matrix operand typename LayoutB_, /// Access granularity of B matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC_, /// Layout type for C and D matrix operands typename LayoutC_, /// Element type for internal accumulation typename ElementAccumulator, /// Operator class tag typename OperatorClass, /// Tag indicating architecture to tune for typename ArchTag, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of stages used in the pipelined mainloop int Stages, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear = SharedMemoryClearOption::kNone, /// Gather operand A by using an index array bool GatherA = false, /// Gather operand B by using an index array bool GatherB = false, /// Scatter result D by using an index array bool ScatterD = false, /// Permute result D typename PermuteDLayout = layout::NoPermute, /// typename Enable = void > struct DefaultGemm; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Hopper Architecture template < /// Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of A matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Element type for internal accumulation typename ElementAccumulator, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of stages used in the pipelined mainloop int Stages, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear, /// Gather operand A by using an index array bool GatherA, /// Gather operand B by using an index array bool GatherB, /// Scatter result D by using an index array bool ScatterD, /// Permute result D typename PermuteDLayout > struct DefaultGemm { /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, arch::Sm90, ThreadblockShape, WarpShape, InstructionShape, Stages, Operator, false, SharedMemoryClear, GatherA, GatherB>::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, EpilogueOutputOp::kCount, ScatterD, PermuteDLayout>::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Ampere Architecture template < /// Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of A matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Layout type for C and D matrix operand typename LayoutC, /// Element type for internal accumulation typename ElementAccumulator, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of stages used in the pipelined mainloop int Stages, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear, /// Gather operand A by using an index array bool GatherA, /// Gather operand B by using an index array bool GatherB, /// Scatter result D by using an index array bool ScatterD, /// Permute result D typename PermuteDLayout > struct DefaultGemm { static_assert((platform::is_same::value || platform::is_same>::value), "Epilogue in the kernel level must be row major"); /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, LayoutC, arch::OpClassTensorOp, arch::Sm80, ThreadblockShape, WarpShape, InstructionShape, Stages, Operator, false, SharedMemoryClear, GatherA, GatherB>::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using RegularEpilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, EpilogueOutputOp::kCount, ScatterD, PermuteDLayout>::Epilogue; using Affine2Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOpAffineRankN< 2, ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, EpilogueOutputOp::kCount>::Epilogue; using Epilogue = typename platform::conditional::value, RegularEpilogue, Affine2Epilogue>::type; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Turing Architecture template < /// Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of B matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Element type for internal accumulation typename ElementAccumulator, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// If true, kernel is configured to support serial reduction in the epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear, /// Gather operand A by using an index array bool GatherA, /// Gather operand B by using an index array bool GatherB, /// Scatter result D by using an index array bool ScatterD, /// Permute result D typename PermuteDLayout > struct DefaultGemm< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC, layout::RowMajor, ElementAccumulator, arch::OpClassTensorOp, arch::Sm75, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator, SharedMemoryClear, GatherA, GatherB, ScatterD, PermuteDLayout > { /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, arch::Sm75, ThreadblockShape, WarpShape, InstructionShape, 2, Operator, false, SharedMemoryClear, GatherA, GatherB >::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, EpilogueOutputOp::kCount, ScatterD, PermuteDLayout >::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Ampere Integer Matrix Multiply Interleaved layout template < /// Element type for A matrix operand typename ElementA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Access granularity of B matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of stages used in the pipelined mainloop int Stages, /// Number of Interleaved k int InterleavedK, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear> struct DefaultGemm< ElementA, layout::ColumnMajorInterleaved, kAlignmentA, ElementB, layout::RowMajorInterleaved, kAlignmentB, ElementC, layout::ColumnMajorInterleaved, int32_t, arch::OpClassTensorOp, arch::Sm80, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, Stages, SplitKSerial, Operator, SharedMemoryClear, false, false, false> { using LayoutA = layout::ColumnMajorInterleaved; using LayoutB = layout::RowMajorInterleaved; using LayoutC = layout::ColumnMajorInterleaved; using ElementAccumulator = int32_t; /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, LayoutC, arch::OpClassTensorOp, arch::Sm80, ThreadblockShape, WarpShape, InstructionShape, Stages, Operator, true, SharedMemoryClear>::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock:: DefaultInterleavedEpilogueTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, 64 / sizeof_bits::value, InterleavedK>::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Turing Integer Matrix Multiply Interleaved layout template < /// Element type for A matrix operand typename ElementA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Access granularity of B matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of Interleaved k int InterleavedK, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear> struct DefaultGemm, kAlignmentA, ElementB, layout::RowMajorInterleaved, kAlignmentB, ElementC, layout::ColumnMajorInterleaved, int32_t, arch::OpClassTensorOp, arch::Sm75, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator, SharedMemoryClear, false, false, false> { using LayoutA = layout::ColumnMajorInterleaved; using LayoutB = layout::RowMajorInterleaved; using LayoutC = layout::ColumnMajorInterleaved; using ElementAccumulator = int32_t; /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, LayoutC, arch::OpClassTensorOp, arch::Sm75, ThreadblockShape, WarpShape, InstructionShape, 2, Operator, true>::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock:: DefaultInterleavedEpilogueTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, 64 / sizeof_bits::value, InterleavedK>::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Volta architecture template < /// Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of B matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Element type for internal accumulation typename ElementAccumulator, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// If true, kernel is configured to support serial reduction in the epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear, /// Gather operand A by using an index array bool GatherA, /// Gather operand B by using an index array bool GatherB, /// Scatter result D by using an index array bool ScatterD, /// Permute result D typename PermuteDLayout > struct 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, SharedMemoryClear, GatherA, GatherB, ScatterD, PermuteDLayout > { /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, arch::Sm70, ThreadblockShape, WarpShape, GemmShape<8, 8, 4>, 2, Operator, false, SharedMemoryClear, GatherA, GatherB >::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, EpilogueOutputOp::kCount, ScatterD, PermuteDLayout >::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for SIMT template < /// Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of A matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Layout type for C and D matrix operand typename LayoutC, /// Element type for internal accumulation typename ElementAccumulator, /// Tag indicating architecture to tune for typename ArchTag, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// If true, kernel is configured to support serial reduction in the epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear, /// Gather operand A by using an index array bool GatherA, /// Gather operand B by using an index array bool GatherB, /// Scatter result D by using an index array bool ScatterD, /// Permute result D typename PermuteDLayout > struct DefaultGemm< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC, LayoutC, ElementAccumulator, arch::OpClassSimt, ArchTag, ThreadblockShape, WarpShape, GemmShape<1, 1, 1>, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator, SharedMemoryClear, GatherA, GatherB, ScatterD, PermuteDLayout, typename platform::enable_if< ! platform::is_same::value >::type > { static_assert((platform::is_same::value || platform::is_same>::value), "Epilogue in the kernel level must be row major"); /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, LayoutC, arch::OpClassSimt, arch::Sm50, ThreadblockShape, WarpShape, GemmShape<1, 1, 1>, 2, Operator, false, SharedMemoryClear, GatherA, GatherB>::ThreadblockMma; static int const kEpilogueElementsPerAccess = EpilogueOutputOp::kCount; static_assert(kEpilogueElementsPerAccess == 1, "simt epilogue must operate on scalars"); /// Define the epilogue using RegularEpilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimt< ThreadblockShape, typename Mma::Operator, EpilogueOutputOp, kEpilogueElementsPerAccess, ScatterD, PermuteDLayout >::Epilogue; using Affine2Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimtAffineRankN< 2, ThreadblockShape, typename Mma::Operator, EpilogueOutputOp, kEpilogueElementsPerAccess >::Epilogue; using Epilogue = typename platform::conditional::value, RegularEpilogue, Affine2Epilogue>::type; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Ampere template < /// Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of A matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Layout type for C and D matrix operand typename LayoutC, /// Element type for internal accumulation typename ElementAccumulator, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of stages int Stages, /// If true, kernel is configured to support serial reduction in the epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear, /// Gather operand A by using an index array bool GatherA, /// Gather operand B by using an index array bool GatherB, /// Scatter result D by using an index array bool ScatterD, /// Permute result D typename PermuteDLayout > struct DefaultGemm, EpilogueOutputOp, ThreadblockSwizzle, Stages, SplitKSerial, Operator, SharedMemoryClear, GatherA, GatherB, ScatterD, PermuteDLayout> { static_assert((platform::is_same::value || platform::is_same>::value), "Epilogue in the kernel level must be row major"); /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, LayoutC, arch::OpClassSimt, arch::Sm80, ThreadblockShape, WarpShape, GemmShape<1, 1, 1>, Stages, Operator, false, SharedMemoryClear, GatherA, GatherB>::ThreadblockMma; static int const kEpilogueElementsPerAccess = EpilogueOutputOp::kCount; static_assert(kEpilogueElementsPerAccess == 1, "simt epilogue must operate on scalars"); /// Define the epilogue using RegularEpilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimt< ThreadblockShape, typename Mma::Operator, EpilogueOutputOp, kEpilogueElementsPerAccess, ScatterD, PermuteDLayout >::Epilogue; using Affine2Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimtAffineRankN< 2, ThreadblockShape, typename Mma::Operator, EpilogueOutputOp, kEpilogueElementsPerAccess >::Epilogue; using Epilogue = typename platform::conditional::value, RegularEpilogue, Affine2Epilogue>::type; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for SIMT DP4A template < /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of A matrix in units of elements int kAlignmentB, /// Layout type for C matrix operand typename LayoutC, /// Element type for C and D matrix operands typename ElementC, /// Tag indicating architecture to tune for typename ArchTag, /// Element type for internal accumulation typename ElementAccumulator, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear > struct DefaultGemm, EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial, Operator, SharedMemoryClear, false, false, false> { using InstructionShape = GemmShape<1, 1, 4>; using ElementA = int8_t; using ElementB = int8_t; using OperatorClass = arch::OpClassSimt; /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma::ThreadblockMma; static int const kEpilogueElementsPerAccess = EpilogueOutputOp::kCount; static_assert(kEpilogueElementsPerAccess == 1, "simt epilogue must operate on scalars"); /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimt< ThreadblockShape, typename Mma::Operator, EpilogueOutputOp, kEpilogueElementsPerAccess >::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; #if defined(CUTLASS_ARCH_WMMA_ENABLED) //////////////////////////////////////////////////////////////////////////////// /// Partial specialization for Wmma Gemm Kernel template < ///< Element type for A matrix operand typename ElementA, /// Layout type for A matrix operand typename LayoutA, /// Access granularity of A matrix in units of elements int kAlignmentA, /// Element type for B matrix operand typename ElementB, /// Layout type for B matrix operand typename LayoutB, /// Access granularity of A matrix in units of elements int kAlignmentB, /// Element type for C and D matrix operands typename ElementC, /// Layout type for C and D matrix operands typename LayoutC, /// Element type for internal accumulation typename ElementAccumulator, /// Tag indicating architecture to tune for typename ArchTag, /// Threadblock-level tile size (concept: GemmShape) typename ThreadblockShape, /// Warp-level tile size (concept: GemmShape) typename WarpShape, /// Warp-level tile size (concept: GemmShape) typename InstructionShape, /// Epilogue output operator typename EpilogueOutputOp, /// Threadblock-level swizzling operator typename ThreadblockSwizzle, /// Number of stages used in the pipelined mainloop int Stages, /// If true, kernel is configured to support serial reduction in the /// epilogue bool SplitKSerial, /// Operation performed by GEMM typename Operator, /// Use zfill or predicate for out-of-bound cp.async SharedMemoryClearOption SharedMemoryClear > struct DefaultGemm< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC, LayoutC, ElementAccumulator, arch::OpClassWmmaTensorOp, ArchTag, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, Stages, SplitKSerial, Operator, SharedMemoryClear, false, false, false > { /// Define the threadblock-scoped matrix multiply-accumulate using Mma = typename cutlass::gemm::threadblock::DefaultMma< ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementAccumulator, LayoutC, arch::OpClassWmmaTensorOp, ArchTag, ThreadblockShape, WarpShape, InstructionShape, Stages, Operator>::ThreadblockMma; static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK; /// Define the epilogue using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueWmmaTensorOp< ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp, EpilogueOutputOp::kCount >::Epilogue; /// Define the kernel-level GEMM operator. using GemmKernel = kernel::Gemm; }; //////////////////////////////////////////////////////////////////////////////// #endif //CUTLASS_ARCH_WMMA_ENABLED //////////////////////////////////////////////////////////////////////////////// } // namespace kernel } // namespace gemm } // namespace cutlass