mma_tensor_op_wmma.h

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#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/arch/wmma.h"

#if defined(CUTLASS_ARCH_WMMA_ENABLED)

#include "cutlass/wmma_array.h"
#include "cutlass/numeric_types.h"
#include "cutlass/matrix_shape.h"

#include "cutlass/arch/memory_sm75.h"
#include "cutlass/arch/mma_sm75.h"
#include "cutlass/gemm/gemm.h"
#include "cutlass/gemm/warp/mma.h"

#include "cutlass/gemm/warp/mma_tensor_op_policy.h"

#include "cutlass/gemm/warp/mma_tensor_op_tile_iterator_wmma.h"


namespace cutlass {
namespace gemm {
namespace warp {


template < 
  typename Shape_,
  typename ElementA_,
  typename LayoutA_,
  typename ElementB_,
  typename LayoutB_,
  typename ElementC_,
  typename LayoutC_,
  typename Policy_,
  int PartitionsK_ = 1,
  int PartitionsN_ = 1,
  typename Enable = bool
>
class MmaTensorOpWmma {
public:
  using Shape = Shape_;

  using ElementA = ElementA_;

  using LayoutA = LayoutA_;

  using ElementB = ElementB_;

  using LayoutB = LayoutB_;

  using ElementC = ElementC_;

  using LayoutC = LayoutC_;

  using Policy = Policy_;

  using OperatorClass = arch::OpClassTensorOp;

  static int const kThreadCount = 32;

  static int const kPartitionsK = PartitionsK_;

  static int const kPartitionsN = PartitionsN_;

public:

  using IteratorA = MmaTensorOpWmmaMultiplicandTileIterator<
     MatrixShape<Shape::kM, Shape::kK>, Operand::kA, ElementA, LayoutA,
     Policy::OpDelta::kRow, kThreadCount, Policy>;

  using FragmentA = typename IteratorA::Fragment;

  using IteratorB = MmaTensorOpWmmaMultiplicandTileIterator<
     MatrixShape<Shape::kK, Shape::kN>, Operand::kB, ElementB, LayoutB,
     Policy::OpDelta::kRow, kThreadCount, Policy>;

  using FragmentB = typename IteratorB::Fragment;

  using IteratorC = MmaTensorOpWmmaAccumulatorTileIterator<
     MatrixShape<Shape::kM, Shape::kN>, ElementC, LayoutC,
    typename Policy::OpDelta, Policy>;

  using FragmentC = typename IteratorC::Fragment;

private:

  static_assert(
    !(Shape::kM % Policy::Operator::Shape::kM) && 
    !(Shape::kN % Policy::Operator::Shape::kN),
    "Shape of warp-level Wmma must be divisible by operator shape (wmma native size)");

  using WmmaIterations = MatrixShape<
    Shape::kM / Policy::Operator::Shape::kM,
    (Shape::kN / Policy::Operator::Shape::kN / kPartitionsN > 0) ?
     Shape::kN / Policy::Operator::Shape::kN / kPartitionsN :
      1
  >;

public:

  typename Policy::Operator wmma;

public:

  //
  // Methods
  //

  CUTLASS_DEVICE
  MmaTensorOpWmma() {}

  CUTLASS_DEVICE
  void operator()(
    FragmentC &D, 
    FragmentA const &A, 
    FragmentB const &B, 
    FragmentC const &C,
    int const &partitionN_idx = 0) const {

    CUTLASS_PRAGMA_UNROLL
    for (int n = 0; n < WmmaIterations::kColumn; ++n) {
      CUTLASS_PRAGMA_UNROLL
      for (int m = 0; m < WmmaIterations::kRow; ++m) {

        // accumulate wmma mma
        wmma(D[m * WmmaIterations::kColumn + n], A[m], B[n], C[m * WmmaIterations::kColumn + n]);
      }
    }  
  }

};


} // namespace warp
} // namespace gemm
} // namespace cutlass

#endif // if defined(CUTLASS_ARCH_WMMA_ENABLED)