* New updates. * Minor profiler updates Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
150 lines
5.1 KiB
C++
150 lines
5.1 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: BSD-3-Clause
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* 3. Neither the name of the copyright holder nor the names of its
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* contributors may be used to endorse or promote products derived from
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* this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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/*! \file
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\brief Template wraps the vector access iterator concept to load whole vector from tensors in
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memory. This is typically used for per-channel scale and bias in convolution kernels.
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*/
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#pragma once
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#include "cutlass/transform/threadblock/predicated_vector_access_iterator.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace transform {
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namespace threadblock {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename VectorAccessIterator_>
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class VectorIterator {
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public:
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using VectorAccessIterator = VectorAccessIterator_;
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using Shape = typename VectorAccessIterator::Shape;
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using Element = typename VectorAccessIterator::Element;
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using Layout = typename VectorAccessIterator::Layout;
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using TensorCoord = typename Layout::TensorCoord;
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using AccessType = typename VectorAccessIterator::AccessType;
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using TensorRef = typename VectorAccessIterator::TensorRef;
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using Index = typename VectorAccessIterator::Index;
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using LongIndex = typename VectorAccessIterator::LongIndex;
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static int const kElementsPerAccess = VectorAccessIterator::kElementsPerAccess;
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static int const kRowsPerIteration = VectorAccessIterator::kRowsPerIteration;
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static int const kThreads = VectorAccessIterator::kThreads;
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static int const kIterations = VectorAccessIterator::kIterations;
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/// Fragment object to be loaded or stored
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using Fragment = cutlass::Array<
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Element, kElementsPerAccess * kIterations>;
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private:
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/// Internal state
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VectorAccessIterator vector_access_iterator_;
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public:
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/// Constructor
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CUTLASS_HOST_DEVICE
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VectorIterator(
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Element const *ptr,
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TensorCoord extent,
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int thread_idx,
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int warp_idx,
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MatrixCoord const &threadblock_offset = MatrixCoord()
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):
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vector_access_iterator_(ptr, extent, thread_idx, warp_idx, threadblock_offset) { }
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/// Advances to the next tile in memory.
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CUTLASS_HOST_DEVICE
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VectorIterator &operator++() {
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vector_access_iterator_.advance();
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return *this;
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}
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/// Advances to the next tile in memory.
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CUTLASS_HOST_DEVICE
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VectorIterator operator++(int) {
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VectorIterator self(*this);
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operator++();
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return self;
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}
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/// Loads a fragment from memory
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CUTLASS_DEVICE
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void load_with_pointer_offset(Fragment &frag, Index pointer_offset) {
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frag.clear();
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AccessType *frag_ptr = reinterpret_cast<AccessType *>(&frag);
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CUTLASS_PRAGMA_UNROLL
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for (int c = 0; c < kIterations; ++c) {
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cutlass::arch::global_load<
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AccessType,
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sizeof(AccessType)
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>(
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frag_ptr[c],
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vector_access_iterator_.get() + pointer_offset,
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vector_access_iterator_.valid()
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);
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++vector_access_iterator_;
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}
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// }
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}
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/// Loads a fragment from memory
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CUTLASS_DEVICE
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void load(Fragment &frag) {
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vector_access_iterator_.set_iteration_index(0);
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load_with_pointer_offset(frag, 0);
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}
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CUTLASS_DEVICE
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void advance() {
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vector_access_iterator_.advance();
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}
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace threadblock
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} // namespace transform
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} // namespace cutlass
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/////////////////////////////////////////////////////////////////////////////////////////////////
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