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/***************************************************************************************************
* Copyright (c) 2017 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
* 2. 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.
*
* 3. Neither the name of the copyright holder 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 THE COPYRIGHT HOLDER OR CONTRIBUTORS 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 TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
**************************************************************************************************/
/*! \file
\brief Templates implementing computing the addresses of loading small
vectors from the global memory.
*/
#pragma once
#include "cutlass/cutlass.h"
#include "cutlass/array.h"
#include "cutlass/coord.h"
#include "cutlass/layout/pitch_linear.h"
#include "cutlass/layout/matrix.h"
#include "cutlass/layout/tensor.h"
#include "cutlass/matrix_coord.h"
#include "cutlass/matrix_shape.h"
#include "cutlass/tensor_ref.h"
////////////////////////////////////////////////////////////////////////////////
namespace cutlass {
namespace transform {
namespace threadblock {
////////////////////////////////////////////////////////////////////////////////
/// PredicatedVectorAccessIterator
///
template <
/// Shape of the vector accessed by the entire threadblock
typename Shape,
/// Shape of the vector accessed by the warp
typename WarpShape,
/// Type of Element
typename Element,
/// Layout of the vector
typename Layout,
/// Number of elements for each access
int ElementsPerAccess,
/// Support residual tile
bool EnableResidualAccess = false
>
class PredicatedVectorAccessIterator;
////////////////////////////////////////////////////////////////////////////////
/// Vector access iterator specialized for vectors, e.g. scale and bias
/// Thread arrangements are for TensorOps
///
template <
typename Shape_,
typename WarpShape_,
typename Element_,
int ElementsPerAccess,
bool EnableResidualAccess
>
class PredicatedVectorAccessIterator <
Shape_,
WarpShape_,
Element_,
layout::PitchLinear,
ElementsPerAccess,
EnableResidualAccess
> {
public:
using Shape = Shape_;
using WarpShape = WarpShape_;
using Element = Element_;
using Layout = layout::PitchLinear;
using Index = typename Layout::Index;
using LongIndex = typename Layout::LongIndex;
using TensorRef = TensorRef<Element, Layout>;
using TensorView = TensorView<Element, Layout>;
using TensorCoord = typename Layout::TensorCoord;
using ConstPointer = const Element *;
using NonConstPointer = typename platform::remove_const<Element>::type *;
// static int const kElementsPerAccess = 128 / sizeof_bits<Element>::value;
static int const kElementsPerAccess = ElementsPerAccess;
static int const kThreads = 32;
static int const kRowsPerIteration = 8;
static int const kThreadsPerRow = kThreads / kRowsPerIteration;
static int const kThreadsPerRowMask = 0x3;
static int const kIterations = WarpShape::kContiguous / (kThreadsPerRow * kElementsPerAccess);
static int const kWarpCountStrided = Shape::kStrided / WarpShape::kStrided;
using AccessType = AlignedArray<Element, kElementsPerAccess>;
private:
/// Internal pointer type permits fast address arithmetic
using BytePointer = char *;
private:
//
// Data members
//
/// Internal pointer to first access of tile
BytePointer pointer_;
/// Extent of tensor
TensorCoord extent_;
/// pointer offset of each thread
TensorCoord thread_offset_;
/// iteration index
LongIndex iteration_;
/// residual access
bool is_residual_;
/// residual offset of each thread
TensorCoord residual_offset_;
public:
/// Constructs a vector access iterator
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator(
/// Pointer to the start of the vector
ConstPointer pointer,
/// Extent of vector
TensorCoord extent,
/// ID of each participating thread
int thread_id,
/// ID of each participating warp
int warp_id,
/// Initial offset of threadblock
TensorCoord const &threadblock_offset)
: pointer_(reinterpret_cast<BytePointer>(
const_cast<NonConstPointer>(pointer))),
extent_(extent),
is_residual_(false) {
int warp_offset = (warp_id / kWarpCountStrided) * WarpShape::kContiguous;
// Per-thread offset in logical coordinates of tensor
thread_offset_ = threadblock_offset + TensorCoord(warp_offset, 0) +
TensorCoord((thread_id & kThreadsPerRowMask) * kElementsPerAccess, 0);
set_iteration_index(0);
if(EnableResidualAccess) {
// compute residual offset
typename TensorCoord::Index residual_size = extent_.contiguous() % WarpShape::kContiguous;
if (residual_size) {
is_residual_ = true;
residual_offset_ = make_Coord(residual_size, 0);
}
}
}
/// Construct a PredicatedVectorAccessIterator with zero threadblock offset
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator(
/// Pointer to start of vector
ConstPointer pointer,
/// Extent of vector
TensorCoord extent,
///< ID of each participating thread
int thread_id,
/// ID of each participating warp
int warp_id)
: PredicatedVectorAccessIterator(pointer, extent, thread_id, warp_id,
make_Coord(0, 0)) {}
/// Overrides the internal iteration index
CUTLASS_HOST_DEVICE
void set_iteration_index(int index) {
iteration_ = index;
}
/// Advances an iterator along logical dimensions of matrix in units of whole tiles
CUTLASS_DEVICE
void add_tile_offset(
TensorCoord const &tile_offset) {
thread_offset_ =
thread_offset_ +
TensorCoord(WarpShape::kContiguous * tile_offset.contiguous(), 0);
}
/// Returns a pointer
CUTLASS_HOST_DEVICE
AccessType *get() const {
return reinterpret_cast<AccessType *>(
pointer_ +
((thread_offset_.contiguous() + iteration_ * kThreadsPerRow * kElementsPerAccess)
* sizeof_bits<Element>::value / 8));
}
/// Increment and return an instance to self.
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator &operator++() {
++iteration_;
if(iteration_ >= kIterations)
iteration_ = 0;
return *this;
}
/// Increment and return an instance to self.
CUTLASS_HOST_DEVICE
void advance() {
if(EnableResidualAccess && is_residual_) {
is_residual_ = false;
thread_offset_ += residual_offset_;
}
else
add_tile_offset(TensorCoord(1, 0));
}
/// Increment and return an instance to self.
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator operator++(int) {
PredicatedVectorAccessIterator self(*this);
operator++();
return self;
}
/// Returns whether access is valid or not
CUTLASS_HOST_DEVICE
bool valid() {
return ((thread_offset_.contiguous() +
iteration_ * kThreadsPerRow * kElementsPerAccess) < extent_.contiguous());
}
};
////////////////////////////////////////////////////////////////////////////////
/// Specialization of PredicatedVectorAccessIterator for row-major data.
///
template <
typename Shape_,
typename WarpShape_,
typename Element_,
int ElementsPerAccess,
bool EnableResidualAccess
>
class PredicatedVectorAccessIterator<
Shape_,
WarpShape_,
Element_,
layout::RowMajor,
ElementsPerAccess,
EnableResidualAccess
> {
public:
using Shape = Shape_;
using WarpShape = WarpShape_;
using Element = Element_;
using Layout = layout::RowMajor;
using Index = typename Layout::Index;
using LongIndex = typename Layout::LongIndex;
using TensorRef = TensorRef<Element, Layout>;
using TensorView = TensorView<Element, Layout>;
using TensorCoord = typename Layout::TensorCoord;
using ConstPointer = const Element *;
using NonConstPointer = typename platform::remove_const<Element>::type *;
using UnderlyingIterator = PredicatedVectorAccessIterator<
layout::PitchLinearShape<Shape::kColumn, Shape::kRow>,
layout::PitchLinearShape<WarpShape::kColumn, WarpShape::kRow>,
Element,
layout::PitchLinear,
ElementsPerAccess,
EnableResidualAccess>;
using AccessType = typename UnderlyingIterator::AccessType;
static int const kElementsPerAccess = UnderlyingIterator::kElementsPerAccess;
static int const kRowsPerIteration = UnderlyingIterator::kRowsPerIteration;
static int const kThreads = UnderlyingIterator::kThreads;
static int const kIterations = UnderlyingIterator::kIterations;
private:
//
// Data members
//
/// Underlying pitch-linear tile iterator
UnderlyingIterator iterator_;
public:
/// Constructs a TileIterator from its precomputed state, threadblock offset,
/// and thread ID
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator(
///< Pointer to the start of the vector
ConstPointer pointer,
///< Extent of tensor
TensorCoord extent,
///< ID of each participating thread
int thread_id,
///< ID of each participating warp
int warp_id,
///< Initial offset of threadblock
TensorCoord const &threadblock_offset)
: iterator_(pointer, layout::PitchLinearCoord(extent.column(), extent.row()),
thread_id, warp_id,
layout::PitchLinearCoord(threadblock_offset.column(),
threadblock_offset.row())) {}
/// Construct a PredicatedVectorAccessIterator with zero threadblock offset
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator(
ConstPointer pointer, ///< Pointer to the start of the vector
TensorCoord extent, ///< Extent of tensor
int thread_id, ///< ID of each participating thread
int warp_id ///< ID of each participating warp
)
: PredicatedVectorAccessIterator(pointer, extent, thread_id, warp_id,
make_Coord(0, 0)) {}
/// Overrides the internal iteration index
CUTLASS_HOST_DEVICE
void set_iteration_index(int index) { iterator_.set_iteration_index(index); }
/// Advances an iterator along logical dimensions of matrix in units of whole
/// tiles
CUTLASS_HOST_DEVICE
void add_tile_offset(TensorCoord const &tile_offset) {
iterator_.add_tile_offset({tile_offset.column(), tile_offset.row()});
}
/// Returns a pointer
CUTLASS_HOST_DEVICE
AccessType *get() const {
return reinterpret_cast<AccessType *>(iterator_.get());
}
/// Advances to the next tile in memory.
///
/// The first time this method is called, predicates are updated, and the
/// iterator's internal pointer is reverted to the first "steady state" tile.
/// Subsequent calls are lightweight and must only update the internal
/// pointer.
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator &operator++() {
++iterator_;
return *this;
}
/// Advances to the next tile in memory.
///
/// The first time this method is called, predicates are updated, and the
/// iterator's internal pointer is reverted to the first "steady state" tile.
/// Subsequent calls are lightweight and must only update the internal
/// pointer.
CUTLASS_HOST_DEVICE
PredicatedVectorAccessIterator operator++(int) {
PredicatedVectorAccessIterator self(*this);
operator++();
return self;
}
/// Increment and return an instance to self.
CUTLASS_HOST_DEVICE
void advance() {
iterator_.advance();
}
/// Returns whether access is valid or not
CUTLASS_HOST_DEVICE
bool valid() {
return iterator_.valid();
}
};
////////////////////////////////////////////////////////////////////////////////
} // namespace threadblock
} // namespace transform
} // namespace cutlass
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