regular_tile_iterator_pitch_linear_2dthreadtile.h

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#pragma once

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

#include "regular_tile_iterator.h"


namespace cutlass {
namespace transform {
namespace threadblock {

template <
  typename Shape,
  typename Element,
  typename Layout,
  int AdvanceRank,
  typename ThreadMap,
  int Alignment = sizeof_bits<Element>::value * ThreadMap::kElementsPerAccess / 8
>
class RegularTileIterator2dThreadTile;


template <
  typename Shape_,
  typename Element_,
  int AdvanceRank,
  typename ThreadMap_,
  int Alignment
>
class RegularTileIterator2dThreadTile<Shape_, Element_, layout::PitchLinear, AdvanceRank, ThreadMap_, Alignment> {
public:

  using Shape = Shape_;
  using Element = Element_;
  using Layout = layout::PitchLinear;
  static int const kAdvanceRank = AdvanceRank;
  using ThreadMap = ThreadMap_;
  static int const kAlignment = Alignment;

  using Index = typename Layout::Index;
  using LongIndex = typename Layout::LongIndex;

  using TensorRef = TensorRef<Element, Layout>;
  using TensorCoord = typename Layout::TensorCoord;

  using Fragment = Array<Element, ThreadMap::Iterations::kCount * ThreadMap::ThreadAccessShape::kCount>;

  static_assert(kAdvanceRank == 0 || kAdvanceRank == 1, 
    "Advance rank may only be along the contiguous or strided dimensions.");

private:

  //
  // Types
  //
  
  using AccessType = AlignedArray<Element, ThreadMap::ThreadAccessShape::kCount, kAlignment>;

  //
  // Data members
  //

  uint8_t *pointer_;

  Index stride_;

  Index increment_strided_;

  Index increment_advance_;

public:

  CUTLASS_DEVICE
  RegularTileIterator2dThreadTile(): pointer_(nullptr), increment_strided_(0), increment_advance_(0) { }

  CUTLASS_DEVICE
  RegularTileIterator2dThreadTile(
    TensorRef const &ref, 
    int thread_idx,
    int interleave
  ){ 
    
    TensorCoord t = ThreadMap::initial_offset(thread_idx);
    long int offset = t[0] * interleave + t[1] * ref.stride()[0]/interleave;
    pointer_ = reinterpret_cast<uint8_t *>(ref.data() + offset);

    stride_ = ref.stride()[0] / interleave;
    increment_strided_ = (ref.stride()[0] * sizeof_bits<Element>::value / 8) * ThreadMap::Delta::kStrided / interleave;

    increment_advance_ = 
      (kAdvanceRank == 0 ? 
        Shape::kContiguous * sizeof_bits<Element>::value / 8 : 
        Shape::kStrided * (ref.stride()[0] * sizeof_bits<Element>::value / 8) / interleave);
  }

  CUTLASS_DEVICE
  void load_with_pointer_offset(Fragment &frag, Index pointer_offset) {

    AccessType *frag_ptr = reinterpret_cast<AccessType *>(&frag);
    uint8_t const *byte_pointer = pointer_ + pointer_offset * sizeof_bits<Element>::value / 8;

    CUTLASS_PRAGMA_UNROLL
    for (int s = 0; s < ThreadMap::Iterations::kStrided; ++s) {

      AccessType const *access_ptr = reinterpret_cast<AccessType const *>(byte_pointer);

      CUTLASS_PRAGMA_UNROLL
      for (int c = 0; c < ThreadMap::Iterations::kContiguous; ++c) {

          int idx = c + s * ThreadMap::Iterations::kContiguous;
           frag_ptr[idx] = access_ptr[c * ThreadMap::Delta::kContiguous / ThreadMap::ThreadAccessShape::kStrided];
        }

      if (s + 1 < ThreadMap::Iterations::kStrided) {
        byte_pointer += increment_strided_;
      }
    }
  }

  CUTLASS_HOST_DEVICE
  void load(Fragment &frag, TensorCoord const & tile_offset) {
    load_with_pointer_offset(
      frag, 
      tile_offset.contiguous() * Shape::kContiguous / ThreadMap::kElementsPerAccess + 
        tile_offset.strided() * Shape::kStrided * stride_
    );
  }

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

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

    AccessType const *frag_ptr = reinterpret_cast<AccessType const*>(&frag);
    uint8_t *byte_pointer = pointer_ + pointer_offset * sizeof_bits<Element>::value / 8;

    CUTLASS_PRAGMA_UNROLL
    for (int s = 0; s < ThreadMap::Iterations::kStrided; ++s) {

      AccessType *access_ptr = reinterpret_cast<AccessType *>(byte_pointer);

      CUTLASS_PRAGMA_UNROLL
      for (int c = 0; c < ThreadMap::Iterations::kContiguous; ++c) {

          int idx = c + s * ThreadMap::Iterations::kContiguous;
          access_ptr[c * ThreadMap::Delta::kContiguous / ThreadMap::ThreadAccessShape::kStrided] = frag_ptr[idx];
      }

      if (s + 1 < ThreadMap::Iterations::kStrided) {
        byte_pointer += increment_strided_;
      }
    }
  }

  CUTLASS_HOST_DEVICE
  void store(Fragment const &frag, TensorCoord const & tile_offset) {
    store_with_pointer_offset(
      frag,
      tile_offset.contiguous() * Shape::kContiguous + tile_offset.strided() * Shape::kStrided * stride_
    );
  }

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

  CUTLASS_HOST_DEVICE
  RegularTileIterator2dThreadTile &operator++() {
    pointer_ += increment_advance_;
    return *this;
  }

  CUTLASS_HOST_DEVICE
  RegularTileIterator2dThreadTile &operator--() {
    pointer_ -= increment_advance_;
    return *this;
  }

  CUTLASS_HOST_DEVICE
  void add_pointer_offset(LongIndex pointer_offset) {
    pointer_ += pointer_offset;
  }

  CUTLASS_DEVICE
  void add_tile_offset(TensorCoord const &coord) {
    int offset = sizeof_bits<Element>::value *
        (coord.contiguous() * Shape::kContiguous + coord.strided() * Shape::kStrided * stride_) / 8;
    add_pointer_offset(offset);
  }

};


template <
  typename Shape_,
  typename Element_,
  int AdvanceRank,
  typename ThreadMap_,
  int Alignment
>
class RegularTileIterator2dThreadTile<Shape_, Element_, layout::RowMajorInterleaved<4>, AdvanceRank, ThreadMap_, Alignment> {
public:

  using Shape = Shape_;
  using Element = Element_;
  using Layout = layout::RowMajorInterleaved<4>;
  static int const kAdvanceRank = AdvanceRank;
  using ThreadMap = ThreadMap_;
  static int const kAlignment = Alignment;

  using Index = typename Layout::Index;
  using LongIndex = typename Layout::LongIndex;

  using TensorRef = TensorRef<Element, Layout>;
  using TensorCoord = typename Layout::TensorCoord;

  using Fragment = Array<Element, ThreadMap::Iterations::kCount * ThreadMap::ThreadAccessShape::kCount>;

  using Underlying = RegularTileIterator2dThreadTile<
    layout::PitchLinearShape<Shape::kColumn, Shape::kRow>,
    Element,
    layout::PitchLinear,
    (kAdvanceRank == 0 ? 1 : 0),
    ThreadMap,
    kAlignment
  >;

  static_assert(kAdvanceRank == 0 || kAdvanceRank == 1, 
    "Advance rank may only be along the row or column dimensions.");

private:

  Underlying iterator_;

public:

  CUTLASS_DEVICE
  RegularTileIterator2dThreadTile() { }

  CUTLASS_DEVICE
  RegularTileIterator2dThreadTile(
    TensorRef const &ref, 
    int thread_idx
  ):
    iterator_({ref.data(), ref.stride()}, thread_idx, 4) {

  }

  CUTLASS_HOST_DEVICE
  void load_with_pointer_offset(Fragment &frag, Index pointer_offset) {
    iterator_.load_with_pointer_offset(frag, pointer_offset);
  }

  CUTLASS_HOST_DEVICE
  void load(Fragment &frag, TensorCoord const & tile_offset) {
    iterator_.load_with_pointer_offset(frag, {tile_offset.column(), tile_offset.row()});
  }

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

  CUTLASS_HOST_DEVICE
  void store_with_pointer_offset(Fragment const &frag, Index pointer_offset) {
    iterator_.store_with_pointer_offset(frag, pointer_offset);
  }

  CUTLASS_HOST_DEVICE
  void store(Fragment const &frag, TensorCoord const & tile_offset) {
    iterator_.store_with_pointer_offset(frag, {tile_offset.column(), tile_offset.row()});
  }

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

  CUTLASS_HOST_DEVICE
  RegularTileIterator2dThreadTile &operator++() {
    ++iterator_;
    return *this;
  }

  CUTLASS_HOST_DEVICE
  RegularTileIterator2dThreadTile &operator--() {
    --iterator_;
    return *this;
  }

  CUTLASS_HOST_DEVICE
  void add_pointer_offset(LongIndex pointer_offset) {
    iterator_.add_pointer_offset(pointer_offset);
  }

  CUTLASS_DEVICE
  void add_tile_offset(TensorCoord const &coord) {
    iterator_.add_tile_offset({coord.column(), coord.row()});
  }

};


template <
  typename Shape_,
  typename Element_,
  int AdvanceRank,
  typename ThreadMap_,
  int Alignment
>
class RegularTileIterator2dThreadTile<Shape_, Element_, layout::ColumnMajorInterleaved<4>, AdvanceRank, ThreadMap_, Alignment> {
public:

  using Shape = Shape_;
  using Element = Element_;
  using Layout = layout::ColumnMajorInterleaved<4>;
  static int const kAdvanceRank = AdvanceRank;
  using ThreadMap = ThreadMap_;
  static int const kAlignment = Alignment;

  using Index = typename Layout::Index;
  using LongIndex = typename Layout::LongIndex;

  using TensorRef = TensorRef<Element, Layout>;
  using TensorCoord = typename Layout::TensorCoord;

  using Fragment = Array<Element, ThreadMap::Iterations::kCount * ThreadMap::ThreadAccessShape::kCount>;
  using PitchLinearThreadMap = PitchLinearStripminedThreadMap< layout::PitchLinearShape<Shape::kRow, Shape::kColumn>, 
                                  ThreadMap::kThreads, ThreadMap::ThreadAccessShape::kCount >;
                        

  using Underlying = RegularTileIterator2dThreadTile<
    layout::PitchLinearShape<Shape::kRow, Shape::kColumn>,
    Element,
    layout::PitchLinear,
    (kAdvanceRank == 0 ? 0 : 1),
    ThreadMap
  >;

  static_assert(kAdvanceRank == 0 || kAdvanceRank == 1, 
    "Advance rank may only be along the row or column dimensions.");

private:

  Underlying iterator_;

public:

  CUTLASS_DEVICE
  RegularTileIterator2dThreadTile() { }

  CUTLASS_DEVICE
  RegularTileIterator2dThreadTile(
    TensorRef const &ref, 
    int thread_idx
  ):
    iterator_({ref.data(), ref.stride()}, thread_idx, 4) {

  }

  CUTLASS_HOST_DEVICE
  void load_with_pointer_offset(Fragment &frag, Index pointer_offset) {
    iterator_.load_with_pointer_offset(frag, pointer_offset);
  }

  CUTLASS_HOST_DEVICE
  void load(Fragment &frag, TensorCoord const & tile_offset) {
    iterator_.load_with_pointer_offset(frag, {tile_offset.row(), tile_offset.column()});
  }

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

  CUTLASS_HOST_DEVICE
  void store_with_pointer_offset(Fragment const &frag, Index pointer_offset) {
    iterator_.store_with_pointer_offset(frag, pointer_offset);
  }

  CUTLASS_HOST_DEVICE
  void store(Fragment const &frag, TensorCoord const & tile_offset) {
    iterator_.store_with_pointer_offset(frag, {tile_offset.row(), tile_offset.column()});
  }

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

  CUTLASS_HOST_DEVICE
  RegularTileIterator2dThreadTile &operator++() {
    ++iterator_;
    return *this;
  }

  CUTLASS_HOST_DEVICE
  RegularTileIterator2dThreadTile &operator--() {
    --iterator_;
    return *this;
  }

  CUTLASS_HOST_DEVICE
  void add_pointer_offset(LongIndex pointer_offset) {
    iterator_.add_pointer_offset(pointer_offset);
  }

  CUTLASS_DEVICE
  void add_tile_offset(TensorCoord const &coord) {
    iterator_.add_tile_offset({coord.row(), coord.column()});
  }

};


} // namespace threadblock
} // namespace transform
} // namespace cutlass