* CUTLASS 3.7 * clean up changelog --------- Co-authored-by: yuzhai <yuzhai@nvidia.com> Co-authored-by: Haicheng Wu <haichengw@nvidia.com>
183 lines
5.9 KiB
C++
183 lines
5.9 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017 - 2025 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
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/arch/arch.h"
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#include "cutlass/device_kernel.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/gemm/threadblock/threadblock_swizzle.h"
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#include "cutlass/gemm/kernel/gemm_universal.h"
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#include "cutlass/gemm/kernel/default_gemm_universal.h"
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#include "cutlass/gemm/device/default_gemm_configuration.h"
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#include "cutlass/gemm/device/gemm_universal_base.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace gemm {
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namespace device {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename GemvKernel_>
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class Gemv {
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public:
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using GemvKernel = GemvKernel_;
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using ElementA = typename GemvKernel::ElementA;
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using LayoutA = typename GemvKernel::LayoutA;
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using ElementB = typename GemvKernel::ElementB;
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using ElementC = typename GemvKernel::ElementC;
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using ElementAccumulator = typename GemvKernel::ElementAccumulator;
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using EpilogueOutputOp = typename GemvKernel::EpilogueOutputOp;
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static ComplexTransform const kTransformA = GemvKernel::kTransformA;
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static ComplexTransform const kTransformB = GemvKernel::kTransformB;
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static int const kThreadCount = GemvKernel::kThreadCount;
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static int const kThreadsPerRow = GemvKernel::kThreadsPerRow;
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using Arguments = typename GemvKernel::Arguments;
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using Params = typename GemvKernel::Params;
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private:
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Params params_;
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public:
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/// Constructs the Gemv.
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Gemv() { }
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/// Determines whether the Gemv can execute the given problem.
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static Status can_implement(Arguments const &args) {
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return GemvKernel::can_implement(args);
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}
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/// Gets the workspace size
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static size_t get_workspace_size(Arguments const &args) {
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return 0;
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}
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/// Computes the grid shape
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static dim3 get_grid_shape(Arguments const &args, dim3 const &block) {
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if(platform::is_same<LayoutA, layout::ColumnMajor>::value) {
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return dim3((args.problem_size.row() + (block.x - 1)) / block.x, 1, args.batch_count % 65536);
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}
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else {
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return dim3((args.problem_size.row() + (block.y - 1)) / block.y, 1, args.batch_count % 65536);
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}
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}
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/// Computes the block shape
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static dim3 get_block_shape() {
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if(platform::is_same<LayoutA, layout::ColumnMajor>::value) {
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return dim3(kThreadCount, 1, 1);
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}
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else {
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return dim3(kThreadsPerRow, kThreadCount / kThreadsPerRow, 1);
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}
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}
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/// Initializes Gemv state from arguments.
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Status initialize(Arguments const &args, void *workspace = nullptr, cudaStream_t stream = nullptr) {
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params_ = Params(args);
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return Status::kSuccess;
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}
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/// Lightweight update given a subset of arguments
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Status update(Arguments const &args, void *workspace = nullptr) {
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return params_.update(args);
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}
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/// Runs the kernel using initialized state.
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Status run(cudaStream_t stream = nullptr) {
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dim3 block = get_block_shape();
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dim3 grid = get_grid_shape(params_, block);
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int smem_size = int(sizeof(typename GemvKernel::SharedStorage));
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// Launch
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cutlass::arch::synclog_setup();
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cutlass::Kernel<GemvKernel><<<grid, block, smem_size, stream>>>(params_);
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//
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// Query for errors
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//
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cudaError_t result = cudaGetLastError();
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return result == cudaSuccess ? Status::kSuccess : Status::kErrorInternal;
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}
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/// Runs the kernel using initialized state.
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Status operator()(cudaStream_t stream = nullptr) {
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return run(stream);
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}
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/// Runs the kernel using initialized state.
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Status operator()(
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Arguments const &args,
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void *workspace = nullptr,
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cudaStream_t stream = nullptr) {
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Status status = initialize(args, workspace, stream);
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if (status == Status::kSuccess) {
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status = run(stream);
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}
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return status;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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} // namespace device
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} // namespace gemm
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} // namespace cutlass
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////////////////////////////////////////////////////////////////////////////////
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