mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 05:01:25 +00:00
1441a0a7ee
* something khushbu can help with * v1 v2 works with flatmm develop * v0 v1 v2 numerical error gone * Fixing numerical error, and interchange preshuffle configs to match with flatmm * Refactor GEMM pipeline configurations and integrate preshuffle support - Updated preshuffle pipeline definitions to include multiple versions (V1, V2, V3). - Changed the pipeline constant from CK_TILE_PIPELINE_PRESHUFFLE to CK_TILE_PIPELINE_PRESHUFFLE_V3 in relevant configurations. - Removed obsolete code and comments * clang format * fix vectorloadsize bug * add the Preshuffle3 * update kwarp calculation in gemm utils * update vector size A and B correctly in V2 pipeline; Added few more changes to align with dteng's branch * fix: add CK_GFX950_SUPPORT macro for gfx950 detection * default disable rotating buffer * docs(CHANGELOG): update changelog for rocm 7.0 * Revert "docs(CHANGELOG): update changelog for rocm 7.0" This reverts commit2bc16fff84. * Remove unused Preshuffle V3 pipeline and related code; update gemm function to use Preshuffle V2; clean up comments and formatting in various files. * revert example/ck_tile/flatmm to its original state * remove comment added by second author * switch to xor ALDSDescriptor * modify the MakeALdsDescriptor() * temporary profiling script * getting rid of line marker compiler error * UniversalWeightPreshufflePipelineAgBgCrPolicy now derives from UniversalGemmBasePolicy * add a minor fix for the config * typo fix * Fix formatting in lambda function for WeightPreshufflePipelineAGmemBGmemCRegV2 * revert change in include/ck_tile/ops/flatmm/pipeline/flatmm_pipeline_agmem_bgmem_creg_v1.hpp * revert change in include/ck_tile/core/arch/amd_buffer_addressing.hpp * reenable the GemmSpatiallyLocalTilePartitioner * make GemmConfigPreshuffle_1 for v1 pipeline, GemmConfigPreshuffle_2 for v2 pipeline * remove hardcoded true for preshuffle bool template argument * rename script * remove gemm_profilie.sh script * merge conflict resolve * clang formatted * typo fix * Remove duplicate include of block_gemm_areg_bsmem_creg_v2r1.hpp in gemm.hpp * Remove commented-out code in UniversalWeightPreshufflePipelineAgBgCrPolicy * Fix missing newline at end of file in run_gemm_example.inc * Remove unused barrier call in BlockWeightPreshuffleASmemBSmemCRegV1 * addressing review comments * removing debug code * addressing review comments * Revert "addressing review comments" This reverts commit29c45192ba. * updating tile_engine code * addressing review comments --------- Co-authored-by: amd-khushbu <khuagarw@amd.com> Co-authored-by: ThomasNing <thomas.ning@amd.com>
290 lines
12 KiB
C++
290 lines
12 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2024-2025, 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 <sstream>
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#include <string>
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#include <tuple>
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#include "ck_tile/host.hpp"
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#include "gemm_utils.hpp"
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#include "run_gemm_example.inc"
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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 ELayout,
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bool Persistent,
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typename CDEElementWise>
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float gemm(const ck_tile::GemmHostArgs& args, const ck_tile::stream_config& s)
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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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GemmConfig::PermuteA,
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GemmConfig::PermuteB>;
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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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ELayout,
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GemmConfig::NumWaveGroups>;
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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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ELayout,
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GemmConfig::TransposeC,
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GemmConfig::UseStructuredSparsity,
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Persistent,
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GemmConfig::NumWaveGroups,
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GemmConfig::Preshuffle>;
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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 = args.k_batch * GemmConfig::K_Tile;
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const ck_tile::index_t K_split = (args.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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ELayout,
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CDEElementWise,
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UniversalGemmProblem::kBlockSize,
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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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GemmConfig::NumWaveGroups>>;
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using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
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auto kargs = Kernel::MakeKernelArgs(args);
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dim3 grids;
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if constexpr(Persistent)
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{
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grids = Kernel::MaxOccupancyGridSize(s);
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}
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else
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{
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grids = Kernel::GridSize(args.M, args.N, args.k_batch);
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}
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constexpr dim3 blocks = Kernel::BlockSize();
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if(!Kernel::IsSupportedArgument(kargs))
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{
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throw std::runtime_error("Wrong! Arguments not supported! Skipping gemm!\n");
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}
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if(s.log_level_ > 0)
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{
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std::cout << "Launching kernel with args: " << Kernel::GetName() << '\n'
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<< "shape: " << GemmShape::GetName() << '\n'
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<< "problem: " << UniversalGemmProblem::GetName() << '\n'
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<< "pipeline: " << GemmPipeline::GetName() << '\n'
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<< "grid: {" << grids.x << ", " << grids.y << ", " << grids.z << "}"
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<< ", blocks: {" << blocks.x << ", " << blocks.y << ", " << blocks.z << "}"
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<< std::endl;
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}
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if(s.flush_cache_)
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{
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std::cout << "Flushing cache..." << std::endl;
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ck_tile::HostTensor<ADataType> a_m(ck_tile::host_tensor_descriptor(
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args.M, args.K, args.stride_A, is_row_major(ALayout{})));
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ck_tile::HostTensor<BDataType> b_n(ck_tile::host_tensor_descriptor(
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args.K, args.N, args.stride_B, is_row_major(BLayout{})));
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auto size_a_buffer = a_m.get_element_space_size_in_bytes();
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auto size_b_buffer = b_n.get_element_space_size_in_bytes();
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ck_tile::RotatingMemWrapper<ADataType, BDataType> rotating_mem(
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kargs.as_ptr[0], kargs.bs_ptr[0], s.rotating_count_, size_a_buffer, size_b_buffer);
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rotating_mem.Print();
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auto run_flush_cache = [&]() {
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// flush icache
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ck_tile::flush_icache();
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// rotating mem
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rotating_mem.Next();
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// clear c mem
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if(args.k_batch > 1)
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hipGetErrorString(hipMemsetAsync(
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args.e_ptr, 0, args.M * args.N * sizeof(CDataType), s.stream_id_));
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};
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ave_time = ck_tile::launch_kernel_time_mask(
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s,
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run_flush_cache,
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ck_tile::make_kernel<blocks.x, GemmConfig::kBlockPerCu>(
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Kernel{}, grids, blocks, 0, kargs));
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}
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else
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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<blocks.x, GemmConfig::kBlockPerCu>(
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Kernel{}, grids, blocks, 0, kargs));
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}
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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(args.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 APrecType,
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typename BPrecType = APrecType,
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typename CPrecType = APrecType>
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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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auto [result, arg_parser] = create_args(argc, argv);
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bool preshuffle = GemmConfig::Preshuffle;
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if(preshuffle && (a_layout != "R" || b_layout != "C"))
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{
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throw std::runtime_error(
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"Preshuffle is supported only for A(Row major), B(column major) input matrices!");
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}
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if(a_layout == "R" && b_layout == "C")
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{
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return run_gemm_example_with_layouts<GemmConfig, APrecType, BPrecType, CPrecType>(
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argc, argv, Row{}, Col{}, Row{});
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}
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else
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{
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throw std::runtime_error("Unsupported memory layout for the input matrices!");
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}
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}
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template <template <typename PreType> typename GemmConfig>
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int run_gemm_example(int argc, char* argv[])
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{
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auto [result, arg_parser] = create_args(argc, argv);
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if(!result)
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return -1;
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std::string data_type = arg_parser.get_str("prec");
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std::string a_layout = arg_parser.get_str("a_layout");
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std::string b_layout = arg_parser.get_str("b_layout");
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if(data_type == "fp16")
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{
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return run_gemm_example_prec_type<GemmConfig<ck_tile::half_t>, ck_tile::half_t>(
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a_layout, b_layout, argc, argv);
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}
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else if(data_type == "bf16")
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{
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return run_gemm_example_prec_type<GemmConfig<ck_tile::half_t>, ck_tile::bf16_t>(
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a_layout, b_layout, argc, argv);
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}
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else if(data_type == "fp8")
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{
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return run_gemm_example_prec_type<GemmConfig<ck_tile::fp8_t>,
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ck_tile::fp8_t,
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ck_tile::fp8_t,
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ck_tile::half_t>(a_layout, b_layout, argc, argv);
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}
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else if(data_type == "bf8")
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{
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return run_gemm_example_prec_type<GemmConfig<ck_tile::bf8_t>,
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ck_tile::bf8_t,
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ck_tile::bf8_t,
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ck_tile::half_t>(a_layout, b_layout, argc, argv);
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}
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else
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{
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throw std::runtime_error("Unsupported data type for this operation !!!");
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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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try
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{
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return !run_gemm_example<GemmConfigPreshuffle_2>(argc, argv);
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}
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catch(const std::runtime_error& e)
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{
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std::cerr << "Caught runtime error: " << e.what() << '\n';
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return EXIT_FAILURE;
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}
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}
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