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ck moe gemm implement (#1936)
* port all moe changes from ck_moe_gemm branch * refine codes in the pr * fix tail odd * fix clang format * fix clang format2 * make hot loop scheduler compatible with 16x16 and 32x32 * clang format * fix per token quant * rename moe example * clang format --------- Co-authored-by: coderfeli <coderfeli@163.com>
This commit is contained in:
feli
509
include/ck/tensor_operation/gpu/device/impl/device_moe_gemm.hpp
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509
include/ck/tensor_operation/gpu/device/impl/device_moe_gemm.hpp
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@@ -0,0 +1,509 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <iostream>
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#include <sstream>
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#include "ck/utility/common_header.hpp"
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#include "ck/tensor_description/tensor_descriptor.hpp"
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#include "ck/tensor_description/tensor_descriptor_helper.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/grid/gridwise_moe_gemm.hpp"
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#include "ck/host_utility/device_prop.hpp"
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#include "ck/host_utility/kernel_launch.hpp"
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#include "ck/host_utility/flush_cache.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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template <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 ADataType,
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typename BDataType,
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typename DsDataType,
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typename CDataType,
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typename GemmAccDataType,
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typename CShuffleDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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GemmSpecialization GemmSpec,
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index_t BlockSize,
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index_t MPerBlock,
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index_t NPerBlock,
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index_t KPerBlock,
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index_t AK1,
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index_t BK1,
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index_t MPerXDL,
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index_t NPerXDL,
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index_t MXdlPerWave,
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index_t NXdlPerWave,
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typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
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typename ABlockTransferThreadClusterArrangeOrder,
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typename ABlockTransferSrcAccessOrder,
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index_t ABlockTransferSrcVectorDim,
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index_t ABlockTransferSrcScalarPerVector,
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index_t ABlockTransferDstScalarPerVector_AK1,
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bool ABlockLdsExtraM,
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typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
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typename BBlockTransferThreadClusterArrangeOrder,
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typename BBlockTransferSrcAccessOrder,
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index_t BBlockTransferSrcVectorDim,
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index_t BBlockTransferSrcScalarPerVector,
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index_t BBlockTransferDstScalarPerVector_BK1,
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bool BBlockLdsExtraN,
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index_t CShuffleMXdlPerWavePerShuffle,
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index_t CShuffleNXdlPerWavePerShuffle,
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typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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typename CDEShuffleBlockTransferScalarPerVectors,
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BlockGemmPipelineScheduler BlkGemmPipeSched = BlockGemmPipelineScheduler::Intrawave,
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BlockGemmPipelineVersion BlkGemmPipelineVer = BlockGemmPipelineVersion::v1,
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bool NSwizzle = false,
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bool IsInputGemm = true,
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typename ComputeTypeA = CDataType,
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typename ComputeTypeB = ComputeTypeA,
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typename LDSTypeA = ComputeTypeA,
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typename LDSTypeB = ComputeTypeB>
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struct DeviceMoeGemm : public DeviceGemmMultipleDSplitKBPreShuffle<ALayout,
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BLayout,
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DsLayout,
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CLayout,
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ADataType,
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BDataType,
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DsDataType,
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CDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation>
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{
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static constexpr index_t NumDTensor = DsDataType::Size();
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using GridwiseGemm =
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GridwiseMoeGemm<ALayout,
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BLayout,
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DsLayout,
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CLayout,
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ADataType,
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BDataType,
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GemmAccDataType,
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CShuffleDataType,
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DsDataType,
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CDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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GemmSpec,
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BlockSize,
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MPerBlock,
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NPerBlock,
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KPerBlock,
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AK1,
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BK1,
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MPerXDL,
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NPerXDL,
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MXdlPerWave,
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NXdlPerWave,
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ABlockTransferThreadClusterLengths_AK0_M_AK1,
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ABlockTransferThreadClusterArrangeOrder,
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ABlockTransferSrcAccessOrder,
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ABlockTransferSrcVectorDim,
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ABlockTransferSrcScalarPerVector,
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ABlockTransferDstScalarPerVector_AK1,
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false,
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ABlockLdsExtraM,
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BBlockTransferThreadClusterLengths_BK0_N_BK1,
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BBlockTransferThreadClusterArrangeOrder,
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BBlockTransferSrcAccessOrder,
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BBlockTransferSrcVectorDim,
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BBlockTransferSrcScalarPerVector,
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BBlockTransferDstScalarPerVector_BK1,
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false,
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BBlockLdsExtraN,
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CShuffleMXdlPerWavePerShuffle,
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CShuffleNXdlPerWavePerShuffle,
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CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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CDEShuffleBlockTransferScalarPerVectors,
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BlkGemmPipeSched,
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BlkGemmPipelineVer,
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NSwizzle,
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ComputeTypeA,
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ComputeTypeB,
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LDSTypeA,
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LDSTypeB>;
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using Argument = typename GridwiseGemm::Argument;
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int GetPreShuffleParameters() override { return NPerXDL; }
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// Invoker
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struct Invoker : public BaseInvoker
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{
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float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
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{
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if(stream_config.log_level_ > 0)
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{
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arg.Print();
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}
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if(!GridwiseGemm::CheckValidity(arg))
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{
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throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
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}
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index_t gdx, gdy, gdz;
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std::tie(gdx, gdy, gdz) = GridwiseGemm::CalculateGridSize(arg.M, arg.N);
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float ave_time = 0;
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index_t k_grain = arg.KBatch * KPerBlock;
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index_t K_split = (arg.K + k_grain - 1) / k_grain * KPerBlock;
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const bool has_main_k_block_loop = GridwiseGemm::CalculateHasMainKBlockLoop(K_split);
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const auto RunKernel = [&](const auto& kernel) {
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if(stream_config.flush_cache)
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{
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std::array<std::size_t, NumDTensor> DsSize;
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Argument arg_ = arg;
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const auto a_grid_desc_ak0_m_ak1 = GridwiseGemm::MakeAGridDescriptor_AK0_M_AK1(
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arg_.M, arg_.MPadded, arg_.K, arg_.KPadded, arg_.StrideA, arg_.AK0);
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const auto b_grid_desc_bk0_n_bk1 = GridwiseGemm::MakeBGridDescriptor_BK0_N_BK1(
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arg_.K, arg_.KPadded, arg_.N, arg_.NPadded, arg_.StrideB, arg_.BK0);
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auto size_a_buffer =
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a_grid_desc_ak0_m_ak1.GetElementSpaceSize() * sizeof(ADataType);
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auto size_b_buffer =
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b_grid_desc_bk0_n_bk1.GetElementSpaceSize() * sizeof(BDataType);
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const auto ds_grid_desc_m_n = GridwiseGemm::MakeDsGridDescriptor_M_N(
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arg_.M, arg_.MPadded, arg_.N, arg_.NPadded, arg_.StrideDs);
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static_for<0, NumDTensor, 1>{}([&](auto i) {
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using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
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DsSize[i] = ds_grid_desc_m_n[i].GetElementSpaceSize() * sizeof(DDataType);
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});
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ck::utility::RotatingMemWrapperMultiD<Argument, DsDataType> rotating_mem(
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arg_, stream_config.rotating_count, size_a_buffer, size_b_buffer, DsSize);
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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::utility::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(arg_.KBatch > 1)
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hipGetErrorString(hipMemsetAsync(arg_.p_c_grid,
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0,
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arg_.M * arg_.N * sizeof(CDataType),
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stream_config.stream_id_));
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};
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ave_time = ck::utility::launch_and_time_kernel_with_preprocess<false>(
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stream_config,
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run_flush_cache,
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kernel,
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dim3(gdx, gdy, gdz),
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dim3(BlockSize),
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0,
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arg_);
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}
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else
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{
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if(arg.KBatch > 1)
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hipGetErrorString(hipMemsetAsync(arg.p_c_grid,
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0,
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arg.M * arg.N * sizeof(CDataType),
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stream_config.stream_id_));
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ave_time = launch_and_time_kernel(
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stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, arg);
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}
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};
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constexpr auto estimated_reg_a = MPerBlock * KPerBlock * sizeof(ADataType) / BlockSize /
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4 * (1 + GridwiseGemm::NWave);
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constexpr auto estimated_reg_b =
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NPerBlock * KPerBlock * sizeof(BDataType) / BlockSize / 4 * (2);
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constexpr auto estimated_reg_c =
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MPerBlock * NPerBlock * sizeof(GemmAccDataType) / BlockSize / 4;
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constexpr auto estimated_reg_total =
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estimated_reg_a + estimated_reg_b + estimated_reg_c;
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constexpr index_t minimum_occupancy = (estimated_reg_total >= 256) ? 1 : 2;
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constexpr auto MemoryDataOp =
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IsInputGemm ? InMemoryDataOperationEnum::Set : InMemoryDataOperationEnum::AtomicAdd;
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if(has_main_k_block_loop)
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{
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// Tail number always full
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if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v1)
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{
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{
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if(GridwiseGemm::CalculateKBlockLoopTailNum(K_split) == TailNumber::Odd)
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{
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const auto kernel = kernel_moe_gemm<GridwiseGemm,
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true,
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MemoryDataOp,
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minimum_occupancy,
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IsInputGemm,
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TailNumber::Odd>;
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RunKernel(kernel);
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}
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else
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{
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const auto kernel = kernel_moe_gemm<GridwiseGemm,
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true,
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MemoryDataOp,
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minimum_occupancy,
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IsInputGemm,
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TailNumber::Even>;
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RunKernel(kernel);
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}
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}
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}
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else if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v2 ||
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BlkGemmPipelineVer == BlockGemmPipelineVersion::v3)
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{
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if(GridwiseGemm::CalculateKBlockLoopTailNum(K_split) == TailNumber::Odd)
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{
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const auto kernel = kernel_moe_gemm_2lds<GridwiseGemm,
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true,
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MemoryDataOp,
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minimum_occupancy,
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IsInputGemm,
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TailNumber::Odd>;
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RunKernel(kernel);
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}
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else
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{
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const auto kernel = kernel_moe_gemm_2lds<GridwiseGemm,
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true,
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MemoryDataOp,
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minimum_occupancy,
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IsInputGemm,
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TailNumber::Even>;
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RunKernel(kernel);
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}
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}
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else
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{
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throw std::runtime_error("todo: only v1 & v2 support now");
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}
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}
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#if 1
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else
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{
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// Tail number always 1
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if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v1)
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{
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const auto kernel = kernel_moe_gemm<GridwiseGemm,
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true,
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InMemoryDataOperationEnum::Set,
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minimum_occupancy,
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IsInputGemm,
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TailNumber::Odd>;
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RunKernel(kernel);
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}
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}
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#endif
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return ave_time;
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}
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// polymorphic
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float Run(const BaseArgument* p_arg,
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const StreamConfig& stream_config = StreamConfig{}) override
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{
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return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
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}
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};
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static constexpr bool IsValidCompilationParameter()
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{
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// TODO: properly implement this check
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return true;
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}
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static bool IsSupportedArgument(const Argument& arg)
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{
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// only impl kbatch 1 now
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if(arg.KBatch > 1)
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{
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return false;
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}
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if(!ck::is_xdl_supported())
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{
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return false;
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}
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if(!is_bf16_atomic_supported() && std::is_same_v<CDataType, ck::bhalf_t> && arg.KBatch > 1)
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{
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return false;
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}
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if((arg.K % AK1 != 0 || arg.K % BK1 != 0) && !(GemmSpec == GemmSpecialization::MKPadding ||
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GemmSpec == GemmSpecialization::NKPadding ||
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GemmSpec == GemmSpecialization::MNKPadding ||
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GemmSpec == GemmSpecialization::KPadding))
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{
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return false;
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}
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if(arg.N % NPerBlock != 0 || arg.K % KPerBlock != 0)
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{
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return false;
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}
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return GridwiseGemm::CheckValidity(arg);
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}
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// polymorphic
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bool IsSupportedArgument(const BaseArgument* p_arg) override
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{
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return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
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}
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static auto MakeArgument(const void* p_sorted_token_ids,
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const void* p_sorted_expert_ids,
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const void* p_max_token_id,
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const void* p_a,
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const void* p_b,
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std::array<const void*, NumDTensor> p_ds,
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void* p_c,
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index_t NumTokens,
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index_t TopK,
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index_t M,
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index_t N,
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index_t K,
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index_t StrideA,
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index_t StrideB,
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std::array<index_t, NumDTensor> StrideDs,
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index_t StrideC,
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index_t KBatch,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op,
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CElementwiseOperation c_element_op)
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{
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return Argument{static_cast<const index_t*>(p_sorted_token_ids),
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static_cast<const index_t*>(p_sorted_expert_ids),
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static_cast<const index_t*>(p_max_token_id),
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static_cast<const ADataType*>(p_a),
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static_cast<const BDataType*>(p_b),
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p_ds,
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static_cast<CDataType*>(p_c),
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NumTokens,
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TopK,
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M,
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N,
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K,
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StrideA,
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StrideB,
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StrideDs,
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StrideC,
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KBatch,
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a_element_op,
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b_element_op,
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c_element_op};
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}
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static auto MakeInvoker() { return Invoker{}; }
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// polymorphic
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std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
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const void* p_b,
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std::array<const void*, NumDTensor> p_ds,
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void* p_c,
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index_t M,
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index_t N,
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index_t K,
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index_t StrideA,
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index_t StrideB,
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std::array<ck::index_t, NumDTensor> StrideDs,
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index_t StrideC,
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index_t KBatch,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op,
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CElementwiseOperation c_element_op) override
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{
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return std::make_unique<Argument>(nullptr,
|
||||
nullptr,
|
||||
nullptr,
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||||
static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
p_ds,
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||||
static_cast<CDataType*>(p_c),
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||||
M, // randoms set, no use
|
||||
0,
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||||
M,
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N,
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||||
K,
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||||
StrideA,
|
||||
StrideB,
|
||||
StrideDs,
|
||||
StrideC,
|
||||
KBatch,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op);
|
||||
}
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||||
|
||||
// polymorphic
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||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
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||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
std::map<BlockGemmPipelineScheduler, std::string> BlkGemmPipelineSchedulerToString{
|
||||
{BlockGemmPipelineScheduler::Intrawave, "Intrawave"},
|
||||
{BlockGemmPipelineScheduler::Interwave, "Interwave"}};
|
||||
|
||||
std::map<BlockGemmPipelineVersion, std::string> BlkGemmPipelineVersionToString{
|
||||
{BlockGemmPipelineVersion::v1, "v1"}, {BlockGemmPipelineVersion::v2, "v2"}};
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceMoeGEmm"
|
||||
<< "<"
|
||||
<< getGemmSpecializationString(GemmSpec) << ", "
|
||||
<< std::string(ALayout::name)[0]
|
||||
<< std::string(BLayout::name)[0]
|
||||
<< std::string(CLayout::name)[0]
|
||||
<< ">"
|
||||
<< " BlkSize: "
|
||||
<< BlockSize << ", "
|
||||
<< "BlkTile: "
|
||||
<< MPerBlock<<"x"<<NPerBlock<<"x"<<KPerBlock << ", "
|
||||
<< "WaveTile: "
|
||||
<< MPerXDL<<"x"<<NPerXDL << ", "
|
||||
<< "WaveMap: "
|
||||
<< MXdlPerWave<<"x" << NXdlPerWave<<", "
|
||||
<< "VmemReadVec: "
|
||||
<< ABlockTransferSrcScalarPerVector<<"x"<<BBlockTransferSrcScalarPerVector<<", "
|
||||
<< "BlkGemmPipelineScheduler: "
|
||||
<< BlkGemmPipelineSchedulerToString[BlkGemmPipeSched] << ", "
|
||||
<< "BlkGemmPipelineVersion: "
|
||||
<< BlkGemmPipelineVersionToString[BlkGemmPipelineVer] << ", "
|
||||
<< "BlkGemmPipelinePrefetchStages: "
|
||||
<< GridwiseGemm::BlockwiseGemmPipe::PrefetchStages;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
Reference in New Issue
Block a user