cutlass/include/cutlass/gemm/kernel/default_gemm_sparse.h
ANIKET SHIVAM 66d9cddc83
New updates for 2.11 (#775)
* New updates.

* Minor profiler updates

Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
2023-01-20 16:32:57 -05:00

192 lines
7.8 KiB
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/*! \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/sparse_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_core_sparse_sm80.h"
#include "cutlass/gemm/threadblock/default_sparse_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"
#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>
struct DefaultSparseGemm;
////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////
/// 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,
/// 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>
struct DefaultSparseGemm<ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB, ElementC,
layout::RowMajor, ElementAccumulator, arch::OpClassTensorOp,
arch::Sm80, ThreadblockShape, WarpShape, InstructionShape,
EpilogueOutputOp, ThreadblockSwizzle, Stages, SplitKSerial,
Operator> {
/// Define the threadblock-scoped matrix multiply-accumulate
using Mma = typename cutlass::gemm::threadblock::DefaultSparseMma<
ElementA, LayoutA, kAlignmentA, ElementB, LayoutB, kAlignmentB,
ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, arch::Sm80,
ThreadblockShape, WarpShape, InstructionShape, Stages,
Operator>::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>::Epilogue;
/// Define the kernel-level GEMM operator.
using GemmKernel = kernel::SparseGemm<Mma, Epilogue, ThreadblockSwizzle, SplitKSerial>;
};
////////////////////////////////////////////////////////////////////////////////
} // namespace kernel
} // namespace gemm
} // namespace cutlass