mirror of
https://github.com/ROCm/composable_kernel.git
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59a85cb4bc
* debugging issue * debugging issue * debugging * debugging * reverting debugging code * clang formatted * updating default_config.json * fix ci failure * clang formatted
398 lines
17 KiB
C++
398 lines
17 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 Pipeline, ck_tile::TailNumber TN>
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void try_run(ck_tile::TailNumber tn)
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{
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if constexpr(Pipeline::PrefetchStages > static_cast<int>(TN))
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{
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if(tn == TN)
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, TN>{});
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}
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}
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}
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template <typename ADataType,
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typename BDataType,
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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 CLayout>
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float gemm_calc(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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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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GemmConfig::UseStructuredSparsity>;
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using GemmPipelineProblem =
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ck_tile::GemmPipelineProblem<ADataType, BDataType, AccDataType, GemmShape, Traits>;
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using BaseGemmPipeline = UNIVERSAL_GEMM_PIPELINE<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 =
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[&](const auto has_hot_loop_, const auto tail_number_, 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 = GEMM_PIPELINE_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 = GEMM_PIPELINE<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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AccDataType,
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CDataType,
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CLayout,
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GemmPipelineProblem::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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using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
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auto kargs = Kernel::MakeKernelArgs(args);
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const dim3 grids = Kernel::GridSize(args.M, args.N, args.k_batch);
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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: " << GemmPipelineProblem::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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static constexpr ck_tile::index_t APackedSize =
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std::is_same_v<BDataType, ck_tile::pk_int4_t> ? 2 : 1;
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static constexpr ck_tile::index_t BPackedSize =
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std::is_same_v<BDataType, ck_tile::pk_int4_t> ? 2 : 1;
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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() / APackedSize;
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auto size_b_buffer = b_n.get_element_space_size_in_bytes() / BPackedSize;
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ck_tile::RotatingMemWrapper<ADataType, BDataType> rotating_mem(
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kargs.a_ptr, kargs.b_ptr, 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.c_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_preprocess(
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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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if(has_hot_loop)
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{
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#if(CK_TILE_PIPELINE_DEFAULT == CK_TILE_PIPELINE_COMPUTE_V3)
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if(tail_num == ck_tile::TailNumber::Full)
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Full>{});
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}
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else if(tail_num == ck_tile::TailNumber::Odd)
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Odd>{});
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}
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else if(tail_num == ck_tile::TailNumber::Even)
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Even>{});
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}
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else
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{
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std::ostringstream err;
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err << "For compute pipeline tail number should always be Full, but have \"" << tail_num
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<< "\" which is not supported! PrefetchStages: " << BaseGemmPipeline::PrefetchStages
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<< "\n File: " << __FILE__ << ":" << __LINE__ << ", in function: " << __func__;
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throw std::runtime_error(err.str());
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}
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#elif(CK_TILE_PIPELINE_DEFAULT == CK_TILE_PIPELINE_MEMORY)
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if(tail_num == ck_tile::TailNumber::One)
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::One>{});
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}
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else if(tail_num == ck_tile::TailNumber::Full)
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Full>{});
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}
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auto check_tail = [&](auto... TNs) {
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(try_run<BaseGemmPipeline, decltype(TNs)::value>(tail_num), ...);
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};
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check_tail(ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Two>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Three>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Four>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Five>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Six>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Seven>{});
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#elif(CK_TILE_PIPELINE_DEFAULT == CK_TILE_PIPELINE_COMPUTE_V4)
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if(tail_num == ck_tile::TailNumber::Three)
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{
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RunSplitk(
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ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Three>{});
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}
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else
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{
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RunSplitk(ck_tile::bool_constant<true>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Two>{});
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}
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#endif
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}
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else
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{
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if(tail_num == ck_tile::TailNumber::Full)
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{
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RunSplitk(ck_tile::bool_constant<false>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Full>{});
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}
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else if(tail_num == ck_tile::TailNumber::Odd)
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{
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RunSplitk(ck_tile::bool_constant<false>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Odd>{});
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}
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else if(tail_num == ck_tile::TailNumber::Even)
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{
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RunSplitk(ck_tile::bool_constant<false>{},
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ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Even>{});
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}
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else
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{
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std::ostringstream err;
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err << "Num K loop must be larger than number of prefetech stages."
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<< "\n PrefetchStages: " << BaseGemmPipeline::PrefetchStages
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<< "\n File: " << __FILE__ << ":" << __LINE__ << ", in function: " << __func__;
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throw std::runtime_error(err.str());
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}
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}
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return ave_time;
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}
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template <typename APrecType, typename BPrecType = APrecType, 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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if constexpr(std::is_same_v<BPrecType, ck_tile::pk_int4_t>)
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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<APrecType, BPrecType, CPrecType>(
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argc, argv, Row{}, Col{}, 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_gemm_example_with_layouts<APrecType, BPrecType, CPrecType>(
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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 memory layout for the input matrices when "
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"BPrecType is ck_tile::pk_int4_t!");
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}
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}
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else
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{
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if(a_layout == "R" && b_layout == "R")
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{
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return run_gemm_example_with_layouts<APrecType, BPrecType, CPrecType>(
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argc, argv, Row{}, Row{}, Row{});
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}
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else if(a_layout == "R" && b_layout == "C")
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{
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return run_gemm_example_with_layouts<APrecType, BPrecType, CPrecType>(
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argc, argv, Row{}, Col{}, 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_gemm_example_with_layouts<APrecType, BPrecType, CPrecType>(
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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_gemm_example_with_layouts<APrecType, BPrecType, CPrecType>(
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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 memory layout for the input matrices!");
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}
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}
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}
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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<ck_tile::half_t>(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<ck_tile::bf16_t>(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<ck_tile::fp8_t, ck_tile::fp8_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 == "bf8")
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{
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return run_gemm_example_prec_type<ck_tile::bf8_t, ck_tile::bf8_t, ck_tile::half_t>(
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a_layout, b_layout, argc, argv);
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}
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#if(CK_TILE_PIPELINE_DEFAULT == CK_TILE_PIPELINE_COMPUTE_V3)
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else if(data_type == "pk_int4_t")
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{
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// TODO: Add support for bhalf_t ADataType
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return run_gemm_example_prec_type<ck_tile::half_t, ck_tile::pk_int4_t, ck_tile::half_t>(
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a_layout, b_layout, argc, argv);
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}
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#endif
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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(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 a non-zero code to indicate failure
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return EXIT_FAILURE;
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}
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return EXIT_SUCCESS;
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}
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