mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-05 14:11:29 +00:00
e279e9420e
* docs(README): update readme with new build instructions * feat(grouped_gemm): add support back for non persistent kernel * refactor(grouped_gemm): simplify tensor creation * refactor(grouped_gemm): Persistance is now GemmConfig value for easier management * chore(grouped_gemm): add print statements to ease debugging * WIP(grouped_gemm): add grouped_gemm_preshuffle example and update CMake configuration * fix(tile_gemm_traits): change default value of Preshuffle_ from 0 to false for clarity * WIP(grouped_gemm): add dummy variables to compile the preshuffle pipelines * chore(grouped_gemm): add print statements and variables to debug numerical error with preshuffle * style: clang format work so far * BUG!(grouped_gemm_kernel.hpp): figured out a potential bug in for numerical errors in preshuffle pipeline * fix(grouped_gemm_kernel): add function in the kernel code to dynamically calculate tail_number resolving numerical errors * refactor(gemm_presuffle): make preshuffle pipeline v2 compatible with operator () calls from grouped gemm * chore(grouped_gemm): add/remove debug comments and debug print statements * feat(grouped_gemm): integrate preshuffle pipeline v2 into grouped gemm for all supported shapes * chore(gemm_profile): add new argument combinations * fix: branch cleanup, formatting, refactoring * fix: branch cleanup, formatting, refactoring * chore(changelog): update changelog to reflect new featuer * address review comments & nit
328 lines
15 KiB
C++
328 lines
15 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
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#include <hip/hip_runtime.h>
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#include <cstring>
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#include <iostream>
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#include <ostream>
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#include <string>
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#include <tuple>
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#include <memory>
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#include "ck_tile/core.hpp"
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#include "ck_tile/ops/epilogue.hpp"
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#include "ck_tile/ops/gemm.hpp"
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#include "ck_tile/host.hpp"
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#include "grouped_gemm.hpp"
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template <typename GemmConfig,
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typename ADataType,
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typename BDataType,
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typename DsDataType,
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typename AccDataType,
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typename CDataType,
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typename ALayout,
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typename BLayout,
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typename DsLayout,
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typename CLayout,
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typename CDEElementWise = ck_tile::element_wise::PassThrough>
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float grouped_gemm(const std::vector<grouped_gemm_kargs>& gemm_descs,
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const ck_tile::stream_config& s,
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void* kargs_ptr)
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{
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using GemmShape = ck_tile::TileGemmShape<
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ck_tile::sequence<GemmConfig::M_Tile, GemmConfig::N_Tile, GemmConfig::K_Tile>,
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ck_tile::sequence<GemmConfig::M_Warp, GemmConfig::N_Warp, GemmConfig::K_Warp>,
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ck_tile::
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sequence<GemmConfig::M_Warp_Tile, GemmConfig::N_Warp_Tile, GemmConfig::K_Warp_Tile>>;
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using TilePartitioner =
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ck_tile::GemmSpatiallyLocalTilePartitioner<GemmShape,
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GemmConfig::TileParitionerGroupNum,
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GemmConfig::TileParitionerM01>;
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using Traits = ck_tile::TileGemmTraits<GemmConfig::kPadM,
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GemmConfig::kPadN,
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GemmConfig::kPadK,
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ALayout,
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BLayout,
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CLayout>;
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using GemmUniversalTraits = ck_tile::TileGemmUniversalTraits<GemmConfig::kPadM,
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GemmConfig::kPadN,
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GemmConfig::kPadK,
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GemmConfig::DoubleSmemBuffer,
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ALayout,
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BLayout,
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CLayout,
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GemmConfig::TransposeC>;
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using GemmPipelineProblem =
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ck_tile::GemmPipelineProblem<ADataType, BDataType, AccDataType, GemmShape, Traits>;
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using BaseGemmPipeline = typename PipelineTypeTraits<
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GemmConfig::Pipeline>::template UniversalGemmPipeline<GemmPipelineProblem>;
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const ck_tile::index_t k_grain = gemm_descs[0].k_batch * GemmConfig::K_Tile;
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const ck_tile::index_t K_split = (gemm_descs[0].K + k_grain - 1) / k_grain * GemmConfig::K_Tile;
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const ck_tile::index_t num_loop = TilePartitioner::GetLoopNum(K_split);
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const bool has_hot_loop = BaseGemmPipeline::BlockHasHotloop(num_loop);
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const ck_tile::TailNumber tail_num = BaseGemmPipeline::GetBlockLoopTailNum(num_loop);
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float ave_time{0};
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const auto Run = [&](const auto has_hot_loop_,
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const auto tail_number_,
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const auto memory_operation_) {
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constexpr bool has_hot_loop_v = has_hot_loop_.value;
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constexpr auto tail_number_v = tail_number_.value;
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constexpr auto scheduler = GemmConfig::Scheduler;
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constexpr auto memory_operation = memory_operation_.value;
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using UniversalGemmProblem = ck_tile::UniversalGemmPipelineProblem<ADataType,
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BDataType,
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AccDataType,
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GemmShape,
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GemmUniversalTraits,
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scheduler,
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has_hot_loop_v,
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tail_number_v>;
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using GemmPipeline = typename PipelineTypeTraits<
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GemmConfig::Pipeline>::template GemmPipeline<UniversalGemmProblem>;
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using GemmEpilogue = ck_tile::CShuffleEpilogue<
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ck_tile::CShuffleEpilogueProblem<ADataType,
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BDataType,
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DsDataType,
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AccDataType,
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CDataType,
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DsLayout,
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CLayout,
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CDEElementWise,
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TilePartitioner::MPerBlock,
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TilePartitioner::NPerBlock,
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GemmConfig::M_Warp,
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GemmConfig::N_Warp,
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GemmConfig::M_Warp_Tile,
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GemmConfig::N_Warp_Tile,
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GemmConfig::K_Warp_Tile,
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UniversalGemmProblem::TransposeC,
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memory_operation>>;
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using Kernel = ck_tile::GroupedGemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
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auto kargs = Kernel::MakeKargs(gemm_descs);
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if(!Kernel::IsSupportedArgument(kargs))
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{
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throw std::runtime_error("Kernel arguments not supported!");
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}
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const dim3 blocks = Kernel::BlockSize();
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const dim3 grids = Kernel::GridSize(gemm_descs);
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HIP_CHECK_ERROR(hipMemcpyWithStream(kargs_ptr,
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kargs.data(),
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get_workspace_size(gemm_descs),
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hipMemcpyHostToDevice,
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s.stream_id_));
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if(s.log_level_ > 0)
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{
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std::cout << "Launching kernel: " << Kernel::GetName() << " with args:" << " grid: {"
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<< grids.x << ", " << grids.y << ", " << grids.z << "}" << ", blocks: {"
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<< blocks.x << ", " << blocks.y << ", " << blocks.z << "}" << std::endl;
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}
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ave_time =
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ck_tile::launch_kernel(s,
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ck_tile::make_kernel<GemmConfig::kBlockPerCu>(
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Kernel{},
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grids,
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blocks,
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0,
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ck_tile::cast_pointer_to_constant_address_space(kargs_ptr),
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gemm_descs.size()));
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return ave_time;
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};
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const auto RunSplitk = [&](const auto has_hot_loop_, const auto tail_number_) {
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if(gemm_descs[0].k_batch == 1)
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{
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Run(has_hot_loop_,
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tail_number_,
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ck_tile::integral_constant<ck_tile::memory_operation_enum,
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ck_tile::memory_operation_enum::set>{});
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}
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else
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{
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Run(has_hot_loop_,
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tail_number_,
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ck_tile::integral_constant<ck_tile::memory_operation_enum,
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ck_tile::memory_operation_enum::atomic_add>{});
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}
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};
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BaseGemmPipeline::TailHandler(RunSplitk, has_hot_loop, tail_num);
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return ave_time;
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}
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template <typename GemmConfig,
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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 AccDataType,
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typename CDataType>
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float grouped_gemm_tileloop(const ck_tile::stream_config& s,
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const ck_tile::index_t num_groups,
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void* kargs_ptr,
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bool splitk)
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{
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using GemmShape = ck_tile::TileGemmShape<
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ck_tile::sequence<GemmConfig::M_Tile, GemmConfig::N_Tile, GemmConfig::K_Tile>,
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ck_tile::sequence<GemmConfig::M_Warp, GemmConfig::N_Warp, GemmConfig::K_Warp>,
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ck_tile::
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sequence<GemmConfig::M_Warp_Tile, GemmConfig::N_Warp_Tile, GemmConfig::K_Warp_Tile>>;
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using TilePartitioner =
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ck_tile::GemmSpatiallyLocalTilePartitioner<GemmShape,
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GemmConfig::TileParitionerGroupNum,
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GemmConfig::TileParitionerM01>;
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using GemmUniversalTraits =
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ck_tile::PersistentTileGemmUniversalTraits<GemmConfig::kPadM,
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GemmConfig::kPadN,
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GemmConfig::kPadK,
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GemmConfig::DoubleSmemBuffer,
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ALayout,
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BLayout,
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CLayout>;
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float ave_time{0};
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const auto Run = [&](const auto memory_operation_) {
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constexpr auto scheduler = GemmConfig::Scheduler;
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constexpr auto memory_operation = memory_operation_.value;
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// We create the GEMM pipeline without specifying hotloop or tailnumber.
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// These are automatically run inside the kernel based on the given input data.
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using UniversalGemmProblem = ck_tile::UniversalGemmPipelineProblem<ADataType,
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BDataType,
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AccDataType,
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GemmShape,
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GemmUniversalTraits,
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scheduler>;
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using GemmPipeline = typename PipelineTypeTraits<
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GemmConfig::Pipeline>::template GemmPipeline<UniversalGemmProblem>;
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using GemmEpilogue = ck_tile::CShuffleEpilogue<
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ck_tile::CShuffleEpilogueProblem<ADataType,
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BDataType,
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ck_tile::tuple<>,
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AccDataType,
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CDataType,
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ck_tile::tuple<>,
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CLayout,
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ck_tile::element_wise::PassThrough,
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TilePartitioner::MPerBlock,
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TilePartitioner::NPerBlock,
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GemmConfig::M_Warp,
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GemmConfig::N_Warp,
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GemmConfig::M_Warp_Tile,
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GemmConfig::N_Warp_Tile,
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GemmConfig::K_Warp_Tile,
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UniversalGemmProblem::TransposeC,
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memory_operation>>;
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using Kernel = ck_tile::GroupedGemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
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const dim3 blocks = Kernel::BlockSize();
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const dim3 grids = Kernel::MaxOccupancyGridSize(s);
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if(s.log_level_ > 0)
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{
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std::cout << "Launching kernel: " << Kernel::GetName() << " with args:" << " grid: {"
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<< grids.x << ", " << grids.y << ", " << grids.z << "}" << ", blocks: {"
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<< blocks.x << ", " << blocks.y << ", " << blocks.z << "}" << std::endl;
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}
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ave_time =
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ck_tile::launch_kernel(s,
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ck_tile::make_kernel<GemmConfig::kBlockPerCu>(
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Kernel{},
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grids,
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blocks,
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0,
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ck_tile::cast_pointer_to_constant_address_space(kargs_ptr),
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num_groups));
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return ave_time;
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};
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if(!splitk)
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{
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Run(ck_tile::integral_constant<ck_tile::memory_operation_enum,
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ck_tile::memory_operation_enum::set>{});
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}
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else
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{
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Run(ck_tile::integral_constant<ck_tile::memory_operation_enum,
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ck_tile::memory_operation_enum::atomic_add>{});
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}
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return ave_time;
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}
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#include "run_grouped_gemm_example.inc"
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template <typename GemmConfig, typename PrecType>
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int run_gemm_example_prec_type(std::string a_layout, std::string b_layout, int argc, char* argv[])
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{
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using Row = ck_tile::tensor_layout::gemm::RowMajor;
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using Col = ck_tile::tensor_layout::gemm::ColumnMajor;
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using Types = GemmTypeConfig<PrecType>;
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// Specific type aliases for easy access
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using ADataType = typename Types::ADataType;
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using BDataType = typename Types::BDataType;
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using AccDataType = typename Types::AccDataType;
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using CDataType = typename Types::CDataType;
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if(a_layout == "R" && b_layout == "C")
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{
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return run_grouped_gemm_example_with_layouts<GemmConfig,
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ADataType,
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BDataType,
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CDataType,
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AccDataType>(argc, argv, Row{}, Col{}, Row{});
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}
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else if(a_layout == "R" && b_layout == "R")
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{
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return run_grouped_gemm_example_with_layouts<GemmConfig,
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ADataType,
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BDataType,
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CDataType,
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AccDataType>(argc, argv, Row{}, Row{}, Row{});
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}
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else if(a_layout == "C" && b_layout == "R")
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{
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return run_grouped_gemm_example_with_layouts<GemmConfig,
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ADataType,
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BDataType,
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CDataType,
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AccDataType>(argc, argv, Col{}, Row{}, Row{});
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}
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else if(a_layout == "C" && b_layout == "C")
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{
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return run_grouped_gemm_example_with_layouts<GemmConfig,
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ADataType,
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BDataType,
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CDataType,
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AccDataType>(argc, argv, Col{}, Col{}, Row{});
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}
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else
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{
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throw std::runtime_error("Unsupported data layout configuration for A and B tensors!");
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}
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}
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int main(int argc, char* argv[])
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{
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return !run_grouped_gemm_example<GemmConfigComputeV4>(argc, argv);
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}
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