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https://github.com/ROCm/composable_kernel.git
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[GEMM] Optimization for MI200/300. (#1135)
* Optimize GEMM on MI200/300: 1. Add new blockwise gemm pipeline 2. Add irregular splitk intances * clang format + typo fix * Fix a bug
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Haocong WANG
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <iostream>
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#include <sstream>
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#include "ck/utility/common_header.hpp"
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#include "ck/tensor_description/tensor_descriptor.hpp"
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#include "ck/tensor_description/tensor_descriptor_helper.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v2.hpp"
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#include "ck/host_utility/device_prop.hpp"
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#include "ck/host_utility/kernel_launch.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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// Note: inter-wave loop scheduler is rolled out to c-shuffle version first. Becuase non c-shuffle
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// version currently has compiler issues with register spill which further causes validation
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// failures.
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template <typename ALayout,
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typename BLayout,
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typename CLayout,
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typename ADataType,
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typename BDataType,
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typename CDataType,
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typename GemmAccDataType,
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typename CShuffleDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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GemmSpecialization GemmSpec,
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index_t NumGemmKPrefetchStage,
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index_t BlockSize,
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index_t MPerBlock,
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index_t NPerBlock,
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index_t KPerBlock,
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index_t AK1,
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index_t BK1,
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index_t MPerXDL,
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index_t NPerXDL,
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index_t MXdlPerWave,
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index_t NXdlPerWave,
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typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
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typename ABlockTransferThreadClusterArrangeOrder,
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typename ABlockTransferSrcAccessOrder,
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index_t ABlockTransferSrcVectorDim,
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index_t ABlockTransferSrcScalarPerVector,
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index_t ABlockTransferDstScalarPerVector_AK1,
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bool ABlockLdsExtraM,
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typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
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typename BBlockTransferThreadClusterArrangeOrder,
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typename BBlockTransferSrcAccessOrder,
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index_t BBlockTransferSrcVectorDim,
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index_t BBlockTransferSrcScalarPerVector,
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index_t BBlockTransferDstScalarPerVector_BK1,
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bool BBlockLdsExtraN,
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index_t CShuffleMXdlPerWavePerShuffle,
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index_t CShuffleNXdlPerWavePerShuffle,
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typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
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LoopScheduler LoopSched = make_default_loop_scheduler(),
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PipelineVersion PipelineVer = PipelineVersion::v1,
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typename ComputeTypeA = CDataType,
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typename ComputeTypeB = ComputeTypeA>
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struct DeviceGemm_Xdl_CShuffleV2 : public DeviceGemm<ALayout,
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BLayout,
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CLayout,
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ADataType,
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BDataType,
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CDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation>
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{
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using DeviceOp = DeviceGemm_Xdl_CShuffleV2;
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static constexpr auto I0 = Number<0>{};
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static constexpr auto I1 = Number<1>{};
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static constexpr auto I2 = Number<2>{};
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// GridwiseGemm
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using GridwiseGemm = GridwiseGemm_xdl_cshuffle_v2<
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ALayout,
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BLayout,
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CLayout,
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ADataType,
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BDataType,
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GemmAccDataType,
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CShuffleDataType,
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CDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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GemmSpec,
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InMemoryDataOperationEnum::Set,
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NumGemmKPrefetchStage,
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BlockSize,
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MPerBlock,
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NPerBlock,
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KPerBlock,
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AK1,
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BK1,
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MPerXDL,
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NPerXDL,
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MXdlPerWave,
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NXdlPerWave,
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ABlockTransferThreadClusterLengths_AK0_M_AK1,
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ABlockTransferThreadClusterArrangeOrder,
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ABlockTransferSrcAccessOrder,
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ABlockTransferSrcVectorDim,
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ABlockTransferSrcScalarPerVector,
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ABlockTransferDstScalarPerVector_AK1,
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false,
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ABlockLdsExtraM,
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BBlockTransferThreadClusterLengths_BK0_N_BK1,
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BBlockTransferThreadClusterArrangeOrder,
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BBlockTransferSrcAccessOrder,
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BBlockTransferSrcVectorDim,
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BBlockTransferSrcScalarPerVector,
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BBlockTransferDstScalarPerVector_BK1,
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false,
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BBlockLdsExtraN,
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CShuffleMXdlPerWavePerShuffle,
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CShuffleNXdlPerWavePerShuffle,
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CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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CShuffleBlockTransferScalarPerVector_NPerBlock,
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LoopSched,
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PipelineVer,
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ComputeTypeA,
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ComputeTypeB>;
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using Argument = typename GridwiseGemm::Argument;
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// Invoker
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struct Invoker : public BaseInvoker
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{
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float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
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{
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if(stream_config.log_level_ > 0)
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{
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arg.Print();
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}
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if(!GridwiseGemm::CheckValidity(arg))
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{
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throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
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}
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index_t gdx, gdy, gdz;
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std::tie(gdx, gdy, gdz) = GridwiseGemm::CalculateGridSize(arg.M, arg.N);
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float ave_time = 0;
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const auto K = GridwiseGemm::CalculateAK0(arg.K) * AK1;
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if(GridwiseGemm::CalculateKBlockLoopTailNum(K) == 3)
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{
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const auto kernel = kernel_gemm_xdl_cshuffle_v2<GridwiseGemm, true>;
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ave_time = launch_and_time_kernel(
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stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, arg);
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}
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else
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{
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const auto kernel = kernel_gemm_xdl_cshuffle_v2<GridwiseGemm, true, 2>;
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ave_time = launch_and_time_kernel(
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stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, arg);
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}
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return ave_time;
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}
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// polymorphic
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float Run(const BaseArgument* p_arg,
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const StreamConfig& stream_config = StreamConfig{}) override
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{
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return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
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}
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};
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static constexpr bool IsValidCompilationParameter()
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{
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// TODO: properly implement this check
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return true;
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}
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static bool IsSupportedArgument(const Argument& arg)
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{
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if(!ck::is_xdl_supported())
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{
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return false;
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}
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if((arg.K % AK1 != 0 || arg.K % BK1 != 0) && !(GemmSpec == GemmSpecialization::MKPadding ||
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GemmSpec == GemmSpecialization::NKPadding ||
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GemmSpec == GemmSpecialization::MNKPadding ||
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GemmSpec == GemmSpecialization::KPadding))
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{
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return false;
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}
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return GridwiseGemm::CheckValidity(arg);
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}
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// polymorphic
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bool IsSupportedArgument(const BaseArgument* p_arg) override
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{
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return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
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}
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static auto MakeArgument(const ADataType* p_a,
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const BDataType* p_b,
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CDataType* p_c,
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index_t M,
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index_t N,
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index_t K,
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index_t StrideA,
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index_t StrideB,
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index_t StrideC,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation)
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{
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return Argument{p_a, p_b, p_c, M, N, K, StrideA, StrideB, StrideC};
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}
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static auto MakeInvoker() { return Invoker{}; }
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// polymorphic
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std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
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const void* p_b,
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void* p_c,
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index_t M,
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index_t N,
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index_t K,
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index_t StrideA,
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index_t StrideB,
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index_t StrideC,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation) override
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{
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return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
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static_cast<const BDataType*>(p_b),
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static_cast<CDataType*>(p_c),
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M,
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N,
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K,
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StrideA,
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StrideB,
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StrideC);
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}
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// polymorphic
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std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
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{
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return std::make_unique<Invoker>(Invoker{});
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}
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// polymorphic
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std::string GetTypeString() const override
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{
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auto str = std::stringstream();
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std::map<LoopScheduler, std::string> LoopSchedToString{
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{LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
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std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
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{PipelineVersion::v2, "v2"}};
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// clang-format off
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str << "DeviceGemm_Xdl_CShuffleV2"
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<< "<"
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<< getGemmSpecializationString(GemmSpec) << ", "
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<< BlockSize << ", "
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<< MPerBlock << ", "
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<< NPerBlock << ", "
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<< KPerBlock << ", "
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<< AK1 << ", "
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<< BK1 << ", "
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<< MPerXDL << ", "
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<< NPerXDL << ", "
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<< MXdlPerWave << ", "
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<< NXdlPerWave << ", "
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<< ABlockTransferSrcScalarPerVector << ", "
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<< BBlockTransferSrcScalarPerVector << ", "
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<< CShuffleMXdlPerWavePerShuffle << ", "
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<< CShuffleNXdlPerWavePerShuffle
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<< ">"
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<< " LoopScheduler: "
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<< LoopSchedToString[LoopSched] << ", "
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<< "PipelineVersion: "
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<< PipelineVersionToString[PipelineVer];
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// clang-format on
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return str.str();
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}
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};
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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