default_gemm_grouped_softmax_mainloop_fusion.h

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/*! \file
    \brief 
      Default kernel-level softmax-grouped-GEMM
*/

#pragma once

#include "cutlass/cutlass.h"

#include "cutlass/complex.h"
#include "cutlass/layout/matrix.h"
#include "cutlass/numeric_types.h"

#include "cutlass/gemm/kernel/gemm_grouped_softmax_mainloop_fusion.h"
#include "cutlass/gemm/kernel/gemm_transpose_operands.h"
#include "cutlass/gemm/kernel/default_gemm.h"
#include "cutlass/gemm/kernel/default_gemm_complex.h"
#include "cutlass/gemm/device/default_gemm_configuration.h"
#include "cutlass/gemm/threadblock/default_mma_softmax_mainloop_fusion.h"

#include "cutlass/layout/permute.h"

/////////////////////////////////////////////////////////////////////////////////////////////////

namespace cutlass {
namespace gemm {
namespace kernel {

/////////////////////////////////////////////////////////////////////////////////////////////////

template <
    /// Element type for A matrix operand
    typename ElementA_,
    /// Layout type for A matrix operand
    typename LayoutA_,
    /// Complex elementwise transformation on A operand
    ComplexTransform TransformA,
    /// 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_,
    /// Complex elementwise transformation on B operand
    ComplexTransform TransformB,
    /// Access granularity of B matrix in units of elements
    int kAlignmentB,
    /// Element type for Scale/Bias vectors
    typename ElementScaleBias_,
    /// Layout type for Scale/Bias vectors
    typename LayoutScaleBias_,
    /// 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,
    /// Whether the schedule of problems to visit has been precomputed
    GroupScheduleMode GroupScheduleMode_ = GroupScheduleMode::kDeviceOnly,
    /// Operation performed by GEMM
    typename Operator = typename device::DefaultGemmConfiguration<
        OperatorClass, ArchTag, ElementA_, ElementB_, ElementC_,
        ElementAccumulator>::Operator,
    /// Use zfill or predicate for out-of-bound cp.async
    SharedMemoryClearOption SharedMemoryClear = SharedMemoryClearOption::kNone
    >
struct DefaultGemmGroupedSoftmaxMainloopFusion {
  // If true, we must construct a 'transposed-and-exchanged' Mma operator.
  static bool const kInternalTranspose = platform::is_same<LayoutC_, layout::ColumnMajor>::value;

  using MapArguments = kernel::detail::MapArguments<
    ElementA_,
    LayoutA_,
    ComplexTransform::kNone,
    kAlignmentA,
    ElementB_,
    LayoutB_,
    ComplexTransform::kNone,
    kAlignmentB,
    LayoutC_,
    kInternalTranspose
  >;

private:
  /// Define the threadblock-scoped matrix multiply-accumulate
  using Mma = typename cutlass::gemm::threadblock::DefaultMmaSoftmaxMainloopFusion<
      typename MapArguments::ElementA, typename MapArguments::LayoutA, MapArguments::kAlignmentA,
      typename MapArguments::ElementB, typename MapArguments::LayoutB, MapArguments::kAlignmentB,
      ElementScaleBias_, LayoutScaleBias_, ElementAccumulator, layout::RowMajor, OperatorClass, ArchTag,
      ThreadblockShape, WarpShape, InstructionShape, Stages, kInternalTranspose,
      Operator, false, SharedMemoryClear>::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;

public:
  using GemmKernel = kernel::GemmGroupedSoftmaxMainloopFusion<
    Mma,
    Epilogue,
    ThreadblockSwizzle,
    GroupScheduleMode_,
    kInternalTranspose
  >;
};

/////////////////////////////////////////////////////////////////////////////////////////////////

}  // namespace kernel
}  // namespace gemm
}  // namespace cutlass

/////////////////////////////////////////////////////////////////////////////////////////////////