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Ding, Yi
323
example/ck_tile/03_gemm/universal_gemm_invoker.hpp
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323
example/ck_tile/03_gemm/universal_gemm_invoker.hpp
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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#include <functional>
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#include <chrono>
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#include <thread>
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#include "gemm_utils.hpp"
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#include "ck_tile/host/hip_check_error.hpp"
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#include "ck_tile/host/device_memory.hpp"
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struct UniversalInvoker
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{
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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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static 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 GemmUniversalTraits =
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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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constexpr auto scheduler = GemmConfig::Scheduler;
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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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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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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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GemmConfig::NumWaveGroups,
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false, /*FixedVectorSize_*/
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1, /*VectorSizeC_*/
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false, /*TiledMMAPermuteN_*/
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1, /*BlockedXDLN_PerWarp_*/
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GemmConfig::DoubleSmemBuffer /*DoubleSmemBuffer*/>>;
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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 = Persistent ? Kernel::MaxOccupancyGridSize(s)
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: Kernel::GridSize(args.M, args.N, args.k_batch);
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const 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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// Declare rotating_mem_ptr here so it stays in scope until it is needed
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std::unique_ptr<ck_tile::RotatingMemWrapper<ADataType, BDataType>> rotating_mem_ptr;
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std::function<void()> preprocess;
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auto clear_gemm_output = [&]() {
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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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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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rotating_mem_ptr = std::make_unique<ck_tile::RotatingMemWrapper<ADataType, BDataType>>(
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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_ptr->Print();
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preprocess = [&]() {
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ck_tile::flush_icache();
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rotating_mem_ptr->Next();
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clear_gemm_output();
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};
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}
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else
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{
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preprocess = clear_gemm_output;
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}
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return ck_tile::launch_kernel_time_mask(
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s,
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preprocess,
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ck_tile::make_kernel<GemmConfig::kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
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}
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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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typename CDEElementWise>
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static void test_async_input_scheduler(const ck_tile::GemmHostArgs& args,
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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 GemmUniversalTraits =
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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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true, // Persistent = true for async test
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GemmConfig::NumWaveGroups,
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GemmConfig::Preshuffle>;
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constexpr auto scheduler = GemmConfig::Scheduler;
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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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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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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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GemmConfig::NumWaveGroups,
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false, /*FixedVectorSize_*/
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1, /*VectorSizeC_*/
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false, /*TiledMMAPermuteN_*/
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1, /*BlockedXDLN_PerWarp_*/
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GemmConfig::DoubleSmemBuffer>>;
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using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
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const ck_tile::index_t tiles_m =
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ck_tile::integer_divide_ceil(args.M, TilePartitioner::MPerBlock);
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// Balance signal granularity (smaller chunks = finer control) vs overhead (more signals)
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const ck_tile::index_t tiles_per_chunk = 2;
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// Shift chunk assignments to test wraparound behavior
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const ck_tile::index_t tile_idx_pivot = tiles_per_chunk;
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// Account for pivot when allocating signal buffer
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const ck_tile::index_t num_chunks =
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ck_tile::integer_divide_ceil(tiles_m + tile_idx_pivot, tiles_per_chunk);
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std::cout << "Async Input Scheduler Test:" << std::endl;
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std::cout << " M tiles: " << tiles_m << std::endl;
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std::cout << " Tiles per chunk: " << tiles_per_chunk << std::endl;
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std::cout << " Tile index pivot: " << tile_idx_pivot << std::endl;
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std::cout << " Number of signal chunks: " << num_chunks << std::endl;
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// Signals must start as zero so kernel blocks until producer sets them
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ck_tile::DeviceMem signal_buf(num_chunks * sizeof(uint32_t));
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signal_buf.SetZero();
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uint32_t* d_chunk_signals = static_cast<uint32_t*>(signal_buf.GetDeviceBuffer());
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// Setup async input scheduler
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ck_tile::PersistentAsyncInputScheduler async_scheduler;
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async_scheduler.tiles_per_chunk_m = tiles_per_chunk;
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async_scheduler.chunk_signals = d_chunk_signals;
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async_scheduler.tile_idx_pivot_m = tile_idx_pivot;
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async_scheduler.num_chunks = num_chunks;
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// Create modified host args with async scheduler
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ck_tile::UniversalGemmHostArgs<1, 1, 0> host_args({args.a_ptr},
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{args.b_ptr},
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{},
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args.e_ptr,
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args.k_batch,
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args.M,
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args.N,
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args.K,
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{args.stride_A},
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{args.stride_B},
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{},
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args.stride_E,
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async_scheduler);
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auto kargs = Kernel::UniversalGemmKernel::MakeKernelArgs(host_args);
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const dim3 grids = Kernel::MaxOccupancyGridSize(s);
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const dim3 blocks = Kernel::BlockSize();
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std::cout << " Grid: {" << grids.x << ", " << grids.y << ", " << grids.z << "}"
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<< std::endl;
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std::cout << " Blocks: {" << blocks.x << ", " << blocks.y << ", " << blocks.z << "}"
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<< std::endl;
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// Separate stream prevents deadlock: kernel and signal producer must run concurrently
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hipStream_t signal_stream;
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HIP_CHECK_ERROR(hipStreamCreateWithFlags(&signal_stream, hipStreamNonBlocking));
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const auto start = std::chrono::high_resolution_clock::now();
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ck_tile::launch_kernel(
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s, ck_tile::make_kernel<GemmConfig::kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
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// Simulate incremental input arrival by delaying signal activation
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const int sleep_us = 100;
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for(ck_tile::index_t i = 0; i < num_chunks; ++i)
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{
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std::this_thread::sleep_for(std::chrono::microseconds(sleep_us));
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const uint32_t signal_val = 1;
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HIP_CHECK_ERROR(hipMemcpyAsync(d_chunk_signals + i,
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&signal_val,
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sizeof(uint32_t),
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hipMemcpyHostToDevice,
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signal_stream));
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}
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HIP_CHECK_ERROR(hipStreamSynchronize(signal_stream));
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HIP_CHECK_ERROR(hipStreamDestroy(signal_stream));
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// Wait for kernel completion
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HIP_CHECK_ERROR(hipDeviceSynchronize());
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auto duration = std::chrono::duration_cast<std::chrono::microseconds>(
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std::chrono::high_resolution_clock::now() - start);
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std::cout << " Total time: " << duration.count() << " us" << std::endl;
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std::cout << " Sleep time: " << (num_chunks * sleep_us) << " us" << std::endl;
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}
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};
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