tile_iterator_wmma_tensor_op.h

Go to the documentation of this file.

/***************************************************************************************************
 * Copyright (c) 2017-2019, NVIDIA CORPORATION.  All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification, are permitted
 * provided that the following conditions are met:
 *     * Redistributions of source code must retain the above copyright notice, this list of
 *       conditions and the following disclaimer.
 *     * Redistributions in binary form must reproduce the above copyright notice, this list of
 *       conditions and the following disclaimer in the documentation and/or other materials
 *       provided with the distribution.
 *     * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
 *       to endorse or promote products derived from this software without specific prior written
 *       permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
 * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
 * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION 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 TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *
 **************************************************************************************************/
#pragma once

#if !defined(__clang__)

#include "cutlass/cutlass.h"
#include "cutlass/wmma_array.h"
#include "cutlass/layout/matrix.h"
#include "cutlass/layout/pitch_linear.h"
#include "cutlass/tensor_ref.h"

#include "cutlass/epilogue/warp/wmma_tensor_op_policy.h"


namespace cutlass {
namespace epilogue {
namespace warp {


template <
  typename WarpShape,           
  typename OperatorShape,       
  typename OperatorFragment,    
  typename Layout               
>
class TileIteratorWmmaTensorOp;


template <
  typename WarpShape_,          
  typename OperatorShape_,      
  typename OperatorFragment_    
>
class TileIteratorWmmaTensorOp<WarpShape_, OperatorShape_, OperatorFragment_, layout::RowMajor> {
public:

  using WarpShape = WarpShape_;
  using OperatorShape = OperatorShape_;
  using OperatorFragment = OperatorFragment_;
  using Layout = layout::RowMajor;

  //
  // Derived types
  //
  using WmmaDataType = typename OperatorFragment::element_type;
  using Element = typename cutlass::arch::WmmaToCutlassDataType<WmmaDataType>::Type; 
  using TensorRef = TensorRef<Element, Layout>;                                      
  using TensorCoord = MatrixCoord;                                                   
  using Index = typename TensorRef::Index;
  using LongIndex = typename TensorRef::LongIndex;

  using Policy = WmmaTensorOpPolicy<WarpShape, OperatorShape, Layout>;

  using Shape = MatrixShape<
    Policy::kRowsPerIteration,
    WarpShape::kN
  >;

  using Fragment = WmmaFragmentArray<OperatorFragment, Policy::OperatorCount::kColumn * Policy::kWmmaFragmentsPerAccess>;


  //using AccumulatorTile = typename Operator::FragmentC;


  // (Epilogue shared memory padding for WMMA Gemm kernel is set to run optimaly on Turing)
  using Padding = MatrixShape<
    0,
    4 * Policy::kElementsPerAccess
  >;

private:

  //using AccessType = AlignedArray<Element, Policy::kElementsPerAccess>;

  //
  // Data members
  //

  TensorRef ref_;


public:

  CUTLASS_HOST_DEVICE
  TileIteratorWmmaTensorOp(): ref_(nullptr) { 

  }

  CUTLASS_HOST_DEVICE
  TileIteratorWmmaTensorOp(
    TensorRef const &ref,
    unsigned lane_id
  ): ref_(ref) {
  }

  CUTLASS_HOST_DEVICE
  TileIteratorWmmaTensorOp & add_pointer_offset(Index pointer_offset) {
    ref_.add_pointer_offset(pointer_offset);
    return *this;
  }

  CUTLASS_HOST_DEVICE
  TileIteratorWmmaTensorOp & add_tile_offset(TensorCoord const &tile_offset) {
    ref_.add_coord_offset({tile_offset.row() * OperatorShape::kM, tile_offset.column() * WarpShape::kN});
    return *this;
  }

  CUTLASS_HOST_DEVICE
  TileIteratorWmmaTensorOp & operator+=(TensorCoord const &tile_offset) {
    add_tile_offset(tile_offset);
    return *this;
  }

  CUTLASS_HOST_DEVICE
  void store_with_pointer_offset(Fragment const &frag, Index pointer_offset) {

    for(int n=0; n < Policy::OperatorCount::kColumn; n++) {
      
      WmmaDataType* ptr = reinterpret_cast<WmmaDataType*> (ref_.data() + ref_.offset({0, n * OperatorShape::kN}) + pointer_offset);

      nvcuda::wmma::store_matrix_sync(
        ptr, 
        frag[n], 
        ref_.stride()[0], 
        nvcuda::wmma::layout_t::mem_row_major
      ); 
    
    }
  }

  CUTLASS_HOST_DEVICE
  void store(Fragment const &frag) {
    store_with_pointer_offset(frag, 0);
  }

  CUTLASS_HOST_DEVICE
  void load_with_pointer_offset(Fragment &frag, Index pointer_offset) const {
 
    for(int n=0; n < Policy::OperatorCount::kColumn; n++) {

      WmmaDataType* ptr = reinterpret_cast<WmmaDataType*> (ref_.data() + ref_.offset({0, n * OperatorShape::kN}) + pointer_offset);

      nvcuda::wmma::load_matrix_sync(         
        frag[n], 
        ptr,
        ref_.stride()[0], 
        nvcuda::wmma::layout_t::mem_row_major
      ); 
    
    }
  }

  CUTLASS_HOST_DEVICE
  void load(Fragment &frag) const {
    load_with_pointer_offset(frag, 0);
  }
};


} // namespace warp
} // namespace epilogue
} // namespace cutlass


#endif // !defined(__clang__)