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Wmma support for gemm_reduce (#3145)
* Initial implementation GEMM+Reduce: - device struct - epilogue struct * Fix tests, improve profiler and add initial instances * Add instances * Fix compilation error * Address review comments * Fix logging --------- Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
This commit is contained in:
Enrico Degregori
@@ -0,0 +1,661 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2025, 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_reduce.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_gemm_wmma_cshuffle_v3.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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namespace ck {
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template <typename GridwiseGemm,
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typename ReduceTrait,
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bool HasMainKBlockLoop,
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InMemoryDataOperationEnum EGlobalMemoryDataOperation,
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index_t MinimumOccupancy = 1,
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TailNumber TailNum = TailNumber::Full>
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__global__ void
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#if CK_USE_LAUNCH_BOUNDS
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__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
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#endif
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kernel_gemm_reduce_wmma_cshuffle_v3(
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typename GridwiseGemm::Argument karg,
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typename ReduceTrait::ReducePtrsGlobal_ p_reduces_grid,
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const typename ReduceTrait::ReduceInElementwiseOperations_ reduce_in_element_ops,
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const typename ReduceTrait::ReduceAccElementwiseOperations_ reduce_out_element_ops)
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{
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#if(defined(__gfx11__) || defined(__gfx12__))
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#if defined(__gfx11__)
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// gfx11 does not support *_atomic_pk_add_f16/bf16 instructions
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using e_data_type = remove_cvref_t<remove_pointer_t<decltype(karg.p_e_grid)>>;
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if constexpr(!(EGlobalMemoryDataOperation == InMemoryDataOperationEnum::AtomicAdd &&
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(std::is_same_v<e_data_type, ck::half_t> ||
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std::is_same_v<e_data_type, ck::bhalf_t>)))
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{
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#endif
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using EpilogueType = typename GridwiseGemm::template EpilogueReduceCShuffle<ReduceTrait>;
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constexpr index_t LDS_size =
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GridwiseGemm::template GetSharedMemoryNumberOfByte<EpilogueType>();
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__shared__ char p_shared[LDS_size];
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auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg, blockIdx.z);
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auto epilogue_args =
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EpilogueType(p_reduces_grid, reduce_in_element_ops, reduce_out_element_ops, karg.M);
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GridwiseGemm::template Run<HasMainKBlockLoop, EGlobalMemoryDataOperation, TailNum>(
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p_shared, splitk_batch_offset, karg, epilogue_args);
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#if defined(__gfx11__)
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}
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#endif
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#else
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ignore = karg;
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ignore = p_reduces_grid;
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ignore = reduce_in_element_ops;
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ignore = reduce_out_element_ops;
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#endif
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}
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} // namespace ck
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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 ELayout,
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typename ADataType,
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typename BDataType,
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typename EDataType,
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typename AccDataType,
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typename CShuffleDataType,
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typename ReduceAccDataType, // Reduce
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typename ReducePtrsGlobal, // Reduce
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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typename ReduceOperations, // Reduce
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typename ReduceInElementwiseOperations, // Reduce
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typename ReduceAccElementwiseOperations, // Reduce
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typename ReduceGlobalMemoryDataOperation, // Reduce
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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 MPerWmma,
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index_t NPerWmma,
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index_t MRepeat,
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index_t NRepeat,
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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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index_t 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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index_t BBlockLdsExtraN,
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index_t CShuffleMRepeatPerShuffle,
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index_t CShuffleNRepeatPerShuffle,
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typename CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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index_t CDEShuffleBlockTransferScalarPerVector,
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typename CReduceThreadClusterLengths_MPerBlock_NPerBlock, // Reduce
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index_t CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock, // Reduce
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index_t CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock, // Reduce
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BlockGemmPipelineScheduler BlkGemmPipeSched = BlockGemmPipelineScheduler::Intrawave,
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BlockGemmPipelineVersion BlkGemmPipelineVer = BlockGemmPipelineVersion::v1,
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typename ComputeTypeA = EDataType,
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typename ComputeTypeB = ComputeTypeA,
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bool PermuteA = false,
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bool PermuteB = false>
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struct DeviceGemmReduce_Wmma_CShuffleV3 : public DeviceGemmReduce<0, ReduceOperations::Size()>
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{
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using CDEShuffleBlockTransferScalarPerVectors =
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Sequence<CDEShuffleBlockTransferScalarPerVector,
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CDEShuffleBlockTransferScalarPerVector,
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CDEShuffleBlockTransferScalarPerVector>;
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using GridwiseGemm = GridwiseGemm_wmma_cshuffle_v3<
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ALayout,
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BLayout,
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Tuple<>,
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ELayout,
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Tuple<ADataType>,
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Tuple<BDataType>,
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AccDataType,
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CShuffleDataType,
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Tuple<>,
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EDataType,
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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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MPerWmma,
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NPerWmma,
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MRepeat,
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NRepeat,
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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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CShuffleMRepeatPerShuffle,
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CShuffleNRepeatPerShuffle,
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CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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CDEShuffleBlockTransferScalarPerVectors,
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BlkGemmPipeSched,
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BlkGemmPipelineVer,
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ComputeTypeA,
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ComputeTypeB,
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PermuteA,
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PermuteB>;
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using ReduceTrait = ReduceTrait_<ReduceAccDataType,
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ReducePtrsGlobal,
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ReduceOperations,
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ReduceInElementwiseOperations,
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ReduceAccElementwiseOperations,
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ReduceGlobalMemoryDataOperation,
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CReduceThreadClusterLengths_MPerBlock_NPerBlock,
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CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock,
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CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock>;
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// Argument
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struct Argument : public BaseArgument
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{
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Argument(const ADataType* p_a_grid,
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const BDataType* p_b_grid,
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EDataType* p_c_grid,
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ReducePtrsGlobal p_reduces_grid,
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index_t MRaw,
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index_t NRaw,
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index_t KRaw,
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index_t StrideA,
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index_t StrideB,
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index_t StrideC,
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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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ReduceInElementwiseOperations reduce_in_element_ops,
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ReduceAccElementwiseOperations reduce_out_element_ops)
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: p_a_grid_{p_a_grid},
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p_b_grid_{p_b_grid},
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p_c_grid_{p_c_grid},
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p_reduces_grid_{p_reduces_grid},
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MRaw_{MRaw},
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NRaw_{NRaw},
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KRaw_{KRaw},
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StrideA_{StrideA},
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StrideB_{StrideB},
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StrideC_{StrideC},
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a_element_op_{a_element_op},
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b_element_op_{b_element_op},
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c_element_op_{c_element_op},
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reduce_in_element_ops_{reduce_in_element_ops},
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reduce_out_element_ops_{reduce_out_element_ops}
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{
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}
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const ADataType* p_a_grid_;
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const BDataType* p_b_grid_;
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EDataType* p_c_grid_;
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ReducePtrsGlobal p_reduces_grid_;
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index_t MRaw_;
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index_t NRaw_;
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index_t KRaw_;
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index_t StrideA_;
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index_t StrideB_;
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index_t StrideC_;
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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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ReduceInElementwiseOperations reduce_in_element_ops_;
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ReduceAccElementwiseOperations reduce_out_element_ops_;
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};
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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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typename GridwiseGemm::Argument gemm_arg{
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std::array<const void*, 1>{arg.p_a_grid_},
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std::array<const void*, 1>{arg.p_b_grid_},
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std::array<const void*, 0>{},
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static_cast<EDataType*>(arg.p_c_grid_),
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arg.MRaw_,
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arg.NRaw_,
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arg.KRaw_,
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std::array<index_t, 1>{arg.StrideA_}, // StrideAs
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std::array<index_t, 1>{arg.StrideB_}, // StrideBs
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std::array<index_t, 0>{}, // StrideDs
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arg.StrideC_, // StrideE
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1, // kbatch
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arg.a_element_op_,
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arg.b_element_op_,
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arg.c_element_op_};
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if(stream_config.log_level_ > 0)
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{
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gemm_arg.Print();
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GridwiseGemm::BlockwiseGemmPipe::HotLoopInstList::Print();
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}
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if(!GridwiseGemm::CheckValidity(gemm_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.MRaw_, arg.NRaw_, 1);
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float ave_time = 0;
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index_t K_split = (arg.KRaw_ + KPerBlock - 1) / KPerBlock * KPerBlock;
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const bool has_main_k_block_loop = GridwiseGemm::CalculateHasMainKBlockLoop(K_split);
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TailNumber TailNum = GridwiseGemm::CalculateKBlockLoopTailNum(arg.KRaw_);
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const auto Run = [&](const auto& kernel) {
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// Note: cache flushing not supported
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ave_time += launch_and_time_kernel(stream_config,
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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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gemm_arg,
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arg.p_reduces_grid_,
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arg.reduce_in_element_ops_,
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arg.reduce_out_element_ops_);
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};
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constexpr index_t minimum_occupancy = []() {
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if constexpr(BlkGemmPipeSched == BlockGemmPipelineScheduler::Interwave)
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{
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return 2;
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}
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else if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v3)
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{
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return (MPerBlock * NPerBlock / BlockSize <= 128) ? 2 : 1;
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}
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else
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{
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return 1;
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}
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}();
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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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BlkGemmPipelineVer == BlockGemmPipelineVersion::v3)
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{
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if(TailNum == TailNumber::Full)
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{
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const auto kernel =
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kernel_gemm_reduce_wmma_cshuffle_v3<GridwiseGemm,
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ReduceTrait,
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true,
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InMemoryDataOperationEnum::Set,
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minimum_occupancy>;
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Run(kernel);
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}
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else
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{
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throw std::runtime_error("wrong! Invalid pipeline setting");
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}
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}
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}
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else
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{
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if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v1)
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{
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if(TailNum == TailNumber::Full)
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{
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const auto kernel =
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kernel_gemm_reduce_wmma_cshuffle_v3<GridwiseGemm,
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ReduceTrait,
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false,
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InMemoryDataOperationEnum::Set,
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minimum_occupancy>;
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Run(kernel);
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}
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else
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{
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throw std::runtime_error("wrong! Invalid pipeline v1 setting");
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}
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}
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else if constexpr(BlkGemmPipelineVer == BlockGemmPipelineVersion::v3)
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{
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if(TailNum == TailNumber::Even)
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{
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const auto kernel =
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kernel_gemm_reduce_wmma_cshuffle_v3<GridwiseGemm,
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ReduceTrait,
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false,
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InMemoryDataOperationEnum::Set,
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minimum_occupancy,
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TailNumber::Even>;
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Run(kernel);
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}
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else if(TailNum == TailNumber::Odd)
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{
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const auto kernel =
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kernel_gemm_reduce_wmma_cshuffle_v3<GridwiseGemm,
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ReduceTrait,
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false,
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InMemoryDataOperationEnum::Set,
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minimum_occupancy,
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TailNumber::Odd>;
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Run(kernel);
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}
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else
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{
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throw std::runtime_error("wrong! Invalid pipeline v3 setting");
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}
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}
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}
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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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if(!ck::is_gfx11_supported() && !ck::is_gfx12_supported())
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{
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if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
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{
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std::cout << "Device implementation supports only gfx11 and gfx12! " << __FILE__
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<< ":" << __LINE__ << ", in function: " << __func__ << std::endl;
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}
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return false;
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}
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if constexpr(std::is_same_v<ComputeTypeA, f8_t> || std::is_same_v<ComputeTypeA, bf8_t> ||
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std::is_same_v<ComputeTypeB, f8_t> || std::is_same_v<ComputeTypeB, bf8_t>)
|
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{
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if(ck::is_gfx11_supported())
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{
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if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
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{
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std::cout << "FP8 and BF8 not supported on gfx11! " << __FILE__ << ":"
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<< __LINE__ << ", in function: " << __func__ << std::endl;
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}
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return false;
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}
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}
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if((arg.KRaw_ % AK1 != 0 || arg.KRaw_ % BK1 != 0) &&
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!(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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if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
|
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{
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std::cout << "Without padding, K must be divisible by AK1 and BK1! " << __FILE__
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<< ":" << __LINE__ << ", in function: " << __func__ << std::endl;
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}
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return false;
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}
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typename GridwiseGemm::Argument gemm_arg{std::array<const void*, 1>{arg.p_a_grid_},
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std::array<const void*, 1>{arg.p_b_grid_},
|
||||
std::array<const void*, 0>{},
|
||||
static_cast<EDataType*>(arg.p_c_grid_),
|
||||
arg.MRaw_,
|
||||
arg.NRaw_,
|
||||
arg.KRaw_,
|
||||
std::array<index_t, 1>{arg.StrideA_}, // StrideAs
|
||||
std::array<index_t, 1>{arg.StrideB_}, // StrideBs
|
||||
std::array<index_t, 0>{}, // StrideDs
|
||||
arg.StrideC_, // StrideE
|
||||
1, // kbatch
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_};
|
||||
|
||||
return GridwiseGemm::CheckValidity(gemm_arg);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
|
||||
static constexpr int NumReduce = ReduceOperations::Size();
|
||||
static auto MakeArgument(const void* p_a,
|
||||
const void* p_b,
|
||||
const void* p_bias,
|
||||
std::array<const void*, 0> p_ds,
|
||||
void* p_c,
|
||||
std::array<void*, NumReduce> p_reduces,
|
||||
ck::index_t M,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t StrideA,
|
||||
ck::index_t StrideB,
|
||||
ck::index_t StrideC,
|
||||
std::array<ck::index_t, 0> StrideDs,
|
||||
std::array<void*, 3> gemm_element_ops,
|
||||
std::array<void*, 0> d_element_ops,
|
||||
std::array<void*, NumReduce> reduce_in_element_op,
|
||||
std::array<void*, NumReduce> reduce_out_element_op)
|
||||
{
|
||||
(void)p_bias;
|
||||
(void)p_ds;
|
||||
(void)StrideDs;
|
||||
(void)d_element_ops;
|
||||
|
||||
ReducePtrsGlobal reduce_tuple = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto tmp = ReducePtrsGlobal{}[I];
|
||||
using T = remove_pointer_t<decltype(tmp)>;
|
||||
return static_cast<T*>(p_reduces[I]);
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
|
||||
ReduceInElementwiseOperations reduce_in_element_ops = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto tmp = ReduceInElementwiseOperations{}[I];
|
||||
using T = remove_pointer_t<decltype(tmp)>;
|
||||
return *(static_cast<T*>(reduce_in_element_op[I]));
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
|
||||
ReduceAccElementwiseOperations reduce_out_element_ops = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto tmp = ReduceAccElementwiseOperations{}[I];
|
||||
using T = remove_pointer_t<decltype(tmp)>;
|
||||
return *(static_cast<T*>(reduce_out_element_op[I]));
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
|
||||
AElementwiseOperation a_element_op =
|
||||
*(static_cast<AElementwiseOperation*>(gemm_element_ops[0]));
|
||||
BElementwiseOperation b_element_op =
|
||||
*(static_cast<BElementwiseOperation*>(gemm_element_ops[1]));
|
||||
CElementwiseOperation c_element_op =
|
||||
*(static_cast<CElementwiseOperation*>(gemm_element_ops[2]));
|
||||
|
||||
return Argument{static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
static_cast<EDataType*>(p_c),
|
||||
reduce_tuple,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
reduce_in_element_ops,
|
||||
reduce_out_element_ops};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(const void* p_a,
|
||||
const void* p_b,
|
||||
const void* p_bias,
|
||||
std::array<const void*, 0> p_ds,
|
||||
void* p_c,
|
||||
std::array<void*, NumReduce> p_reduces,
|
||||
ck::index_t M,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t StrideA,
|
||||
ck::index_t StrideB,
|
||||
ck::index_t StrideC,
|
||||
std::array<ck::index_t, 0> StrideDs,
|
||||
std::array<void*, 3> gemm_element_ops,
|
||||
std::array<void*, 0> d_element_ops,
|
||||
std::array<void*, NumReduce> reduce_in_element_op,
|
||||
std::array<void*, NumReduce> reduce_out_element_op,
|
||||
ck::index_t = 1) override
|
||||
{
|
||||
(void)p_bias;
|
||||
(void)p_ds;
|
||||
(void)StrideDs;
|
||||
(void)d_element_ops;
|
||||
|
||||
ReducePtrsGlobal reduce_tuple = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto tmp = ReducePtrsGlobal{}[I];
|
||||
using T = remove_pointer_t<decltype(tmp)>;
|
||||
return static_cast<T*>(p_reduces[I]);
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
|
||||
ReduceInElementwiseOperations reduce_in_element_ops = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto tmp = ReduceInElementwiseOperations{}[I];
|
||||
using T = remove_pointer_t<decltype(tmp)>;
|
||||
return *(static_cast<T*>(reduce_in_element_op[I]));
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
ReduceAccElementwiseOperations reduce_out_element_ops = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto tmp = ReduceAccElementwiseOperations{}[I];
|
||||
using T = remove_pointer_t<decltype(tmp)>;
|
||||
return *(static_cast<T*>(reduce_out_element_op[I]));
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
|
||||
AElementwiseOperation a_element_op =
|
||||
*(static_cast<AElementwiseOperation*>(gemm_element_ops[0]));
|
||||
BElementwiseOperation b_element_op =
|
||||
*(static_cast<BElementwiseOperation*>(gemm_element_ops[1]));
|
||||
CElementwiseOperation c_element_op =
|
||||
*(static_cast<CElementwiseOperation*>(gemm_element_ops[2]));
|
||||
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
static_cast<EDataType*>(p_c),
|
||||
reduce_tuple,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
reduce_in_element_ops,
|
||||
reduce_out_element_ops);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceGemmReduce_Wmma_CShuffleV3"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< KPerBlock << ", "
|
||||
<< AK1 << ", "
|
||||
<< BK1 << ", "
|
||||
<< MPerWmma << ", "
|
||||
<< NPerWmma << ", "
|
||||
<< MRepeat << ", "
|
||||
<< NRepeat << ", "
|
||||
<< ABlockTransferSrcScalarPerVector << ", "
|
||||
<< BBlockTransferSrcScalarPerVector << ", "
|
||||
<< CShuffleMRepeatPerShuffle << ", "
|
||||
<< CShuffleNRepeatPerShuffle
|
||||
<< ">";
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,470 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "ck/tensor_operation/gpu/grid/epilogue_cshuffle_v3_wmma_base.hpp"
|
||||
#include "ck/tensor_operation/gpu/thread/reduction_functions_threadwise.hpp"
|
||||
|
||||
namespace ck {
|
||||
|
||||
template <typename ReduceAccDataType,
|
||||
typename ReducePtrsGlobal,
|
||||
typename ReduceOperations,
|
||||
typename ReduceInElementwiseOperations,
|
||||
typename ReduceAccElementwiseOperations,
|
||||
typename ReduceGlobalMemoryDataOperation,
|
||||
typename CReduceThreadClusterLengths_MPerBlock_NPerBlock,
|
||||
index_t CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock,
|
||||
index_t CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock>
|
||||
struct ReduceTrait_
|
||||
{
|
||||
using ReduceAccDataType_ = ReduceAccDataType;
|
||||
using ReducePtrsGlobal_ = ReducePtrsGlobal;
|
||||
using ReduceOperations_ = ReduceOperations;
|
||||
using ReduceInElementwiseOperations_ = ReduceInElementwiseOperations;
|
||||
using ReduceAccElementwiseOperations_ = ReduceAccElementwiseOperations;
|
||||
using ReduceGlobalMemoryDataOperation_ = ReduceGlobalMemoryDataOperation;
|
||||
using CReduceThreadClusterLengths_MPerBlock_NPerBlock_ =
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock;
|
||||
static constexpr index_t CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock_ =
|
||||
CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock;
|
||||
static constexpr index_t CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock_ =
|
||||
CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock;
|
||||
};
|
||||
|
||||
template <typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AccDataType,
|
||||
typename CShuffleDataType,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t MPerWmma,
|
||||
index_t NPerWmma,
|
||||
index_t MRepeat,
|
||||
index_t NRepeat,
|
||||
index_t CShuffleMRepeatPerShuffle,
|
||||
index_t CShuffleNRepeatPerShuffle,
|
||||
typename CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename CDEShuffleBlockTransferScalarPerVectors,
|
||||
typename CDEElementwiseOperation,
|
||||
typename ThisThreadBlock,
|
||||
typename BlockwiseGemmPipe,
|
||||
tensor_operation::device::GemmSpecialization GemmSpec,
|
||||
index_t BlockSize,
|
||||
typename ReduceTrait>
|
||||
struct EpilogueReduceCShuffle
|
||||
: EpilogueCShuffleBase<DsDataType,
|
||||
EDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
MPerWmma,
|
||||
NPerWmma,
|
||||
MRepeat,
|
||||
NRepeat,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
CDEElementwiseOperation,
|
||||
ThisThreadBlock,
|
||||
BlockwiseGemmPipe>
|
||||
{
|
||||
using Base = EpilogueCShuffleBase<
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
MPerWmma,
|
||||
NPerWmma,
|
||||
MRepeat,
|
||||
NRepeat,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
CDEElementwiseOperation,
|
||||
ThisThreadBlock,
|
||||
BlockwiseGemmPipe>;
|
||||
|
||||
using Base::GetCShuffleBlockDescriptor_MShRepeat_MPerShRepeat_NShRepeat_NPerShRepeat;
|
||||
using Base::GetCShuffleLDSDescriptor;
|
||||
using Base::GetVgprToLDSEpilogueDescriptor;
|
||||
using Base::I0;
|
||||
using Base::I1;
|
||||
using Base::I3;
|
||||
using Base::NumDTensor;
|
||||
|
||||
// assume Reduce is packed tensor
|
||||
__device__ static auto MakeReduceGridDescriptor_M(index_t MRaw)
|
||||
{
|
||||
using GemmSpecialization = tensor_operation::device::GemmSpecialization;
|
||||
|
||||
const auto d_grid_desc_mraw = make_naive_tensor_descriptor_packed(make_tuple(MRaw));
|
||||
|
||||
const auto M = math::integer_divide_ceil(MRaw, MPerBlock) * MPerBlock;
|
||||
const auto MPad = M - MRaw;
|
||||
|
||||
if constexpr(GemmSpec == GemmSpecialization::MPadding ||
|
||||
GemmSpec == GemmSpecialization::MNPadding ||
|
||||
GemmSpec == GemmSpecialization::MKPadding ||
|
||||
GemmSpec == GemmSpecialization::MNKPadding)
|
||||
{
|
||||
// pad M
|
||||
return transform_tensor_descriptor(d_grid_desc_mraw,
|
||||
make_tuple(make_right_pad_transform(MRaw, MPad)),
|
||||
make_tuple(Sequence<0>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
}
|
||||
else
|
||||
{
|
||||
// not pad M
|
||||
return d_grid_desc_mraw;
|
||||
}
|
||||
}
|
||||
|
||||
using ReduceGridDesc_M = decltype(MakeReduceGridDescriptor_M(1));
|
||||
|
||||
__device__ static constexpr auto
|
||||
MakeReduceGridDescriptor_MBlock_MPerBlock(const ReduceGridDesc_M& d_grid_desc_m)
|
||||
{
|
||||
const auto M = d_grid_desc_m.GetLength(I0);
|
||||
const auto MBlock = M / MPerBlock;
|
||||
|
||||
const auto reduce_grid_desc_mblock_mperblock = transform_tensor_descriptor(
|
||||
d_grid_desc_m,
|
||||
make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{}))),
|
||||
make_tuple(Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 1>{}));
|
||||
|
||||
return reduce_grid_desc_mblock_mperblock;
|
||||
}
|
||||
|
||||
__device__ EpilogueReduceCShuffle(
|
||||
typename ReduceTrait::ReducePtrsGlobal_ p_reduces_grid_,
|
||||
const typename ReduceTrait::ReduceInElementwiseOperations_ reduce_in_element_ops_,
|
||||
const typename ReduceTrait::ReduceAccElementwiseOperations_ reduce_out_element_ops_,
|
||||
const index_t MRaw_)
|
||||
: p_reduces_grid(p_reduces_grid_),
|
||||
reduce_in_element_ops(reduce_in_element_ops_),
|
||||
reduce_out_element_ops(reduce_out_element_ops_),
|
||||
MRaw(MRaw_),
|
||||
reduce_grid_desc_m{MakeReduceGridDescriptor_M(MRaw)}
|
||||
{
|
||||
}
|
||||
|
||||
template <InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
typename CThreadBuf,
|
||||
typename DsGridPointer,
|
||||
typename DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock>
|
||||
__device__ void Run(CThreadBuf& c_thread_buf,
|
||||
DsGridPointer p_ds_grid,
|
||||
EDataType* p_e_grid,
|
||||
void* p_shared,
|
||||
const DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock&
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock&
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
CDEElementwiseOperation& cde_element_op,
|
||||
const index_t& block_m_id,
|
||||
const index_t& block_n_id)
|
||||
{
|
||||
auto reduce_grid_desc_mblock_mperblock =
|
||||
MakeReduceGridDescriptor_MBlock_MPerBlock(reduce_grid_desc_m);
|
||||
|
||||
const auto ds_grid_buf = generate_tuple(
|
||||
[&](auto i) {
|
||||
return make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
p_ds_grid[i],
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock[i].GetElementSpaceSize());
|
||||
},
|
||||
Number<NumDTensor>{});
|
||||
|
||||
auto e_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
p_e_grid, e_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
// C mapping in single thread.
|
||||
constexpr auto c_thread_desc_mrepeat_mwave_msubgroup_nrepeat_nwave_nthreadpersubgroup_maccvgprs =
|
||||
BlockwiseGemmPipe::
|
||||
GetCThreadDescriptor_MRepeat_MWave_MSubGroup_NRepeat_NWave_NThreadPerSubGroup_MAccVgprs();
|
||||
|
||||
// LDS buffer
|
||||
constexpr auto c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat =
|
||||
GetCShuffleBlockDescriptor_MShRepeat_MPerShRepeat_NShRepeat_NPerShRepeat();
|
||||
|
||||
auto c_shuffle_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
|
||||
static_cast<CShuffleDataType*>(p_shared),
|
||||
c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat
|
||||
.GetElementSpaceSize());
|
||||
|
||||
// Thread transfer Vgpr to LDS
|
||||
auto c_thread_copy_vgpr_to_lds = GetVgprToLDSEpilogueDescriptor();
|
||||
|
||||
// Space Filling Curve Vgpr
|
||||
constexpr auto sfc_c_vgpr = typename Base::SpaceFillingCurveVgpr{};
|
||||
|
||||
// Space Filling Curve Vmem
|
||||
constexpr auto sfc_cde_global = typename Base::SpaceFillingCurveVmem{};
|
||||
|
||||
// Block descriptor
|
||||
constexpr auto
|
||||
c_block_desc_mrepeat_mwave_msubgroup_nrepeat_nwave_nthreadpersubgroup_maccvgprs =
|
||||
GetCShuffleLDSDescriptor();
|
||||
|
||||
// tuple of reference to C/Ds tensor descriptors
|
||||
const auto c_ds_desc_refs = concat_tuple_of_reference(
|
||||
tie(c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat),
|
||||
generate_tie([&](auto i) -> const auto& // return type should be reference
|
||||
{ return ds_grid_desc_mblock_mperblock_nblock_nperblock[i]; },
|
||||
Number<NumDTensor>{}));
|
||||
|
||||
// Thread transfer LDS to Vmem
|
||||
auto cde_shuffle_block_copy_lds_and_global =
|
||||
Base::template GetLDSToVmemEpilogueDescriptor<EGlobalMemoryDataOperation, EDataType>(
|
||||
c_ds_desc_refs,
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
cde_element_op,
|
||||
block_m_id,
|
||||
block_n_id);
|
||||
|
||||
// tuple of reference to C/Ds tensor buffers
|
||||
const auto c_ds_buf_refs = concat_tuple_of_reference(
|
||||
tie(c_shuffle_block_buf),
|
||||
generate_tie([&](auto i) -> const auto& // return type should be reference
|
||||
{ return ds_grid_buf[i]; },
|
||||
Number<NumDTensor>{}));
|
||||
|
||||
// LDS c_reduce_block_desc_mperblock_nperblock
|
||||
constexpr auto c_reduce_block_desc_mperblock_nperblock = transform_tensor_descriptor(
|
||||
c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat,
|
||||
make_tuple(
|
||||
make_freeze_transform(I0),
|
||||
make_pass_through_transform(
|
||||
c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat.GetLength(
|
||||
I1)),
|
||||
make_freeze_transform(I0),
|
||||
make_pass_through_transform(
|
||||
c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat.GetLength(
|
||||
I3))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<>{}, Sequence<0>{}, Sequence<>{}, Sequence<1>{}));
|
||||
|
||||
static_assert(
|
||||
ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_::At(I0) *
|
||||
ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_::At(I1) ==
|
||||
BlockSize,
|
||||
"wrong!");
|
||||
|
||||
static_assert(
|
||||
(CShuffleMRepeatPerShuffle * BlockwiseGemmPipe::MWaves * MPerWmma) %
|
||||
ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_::At(I0) ==
|
||||
0 &&
|
||||
(CShuffleNRepeatPerShuffle * BlockwiseGemmPipe::NWaves * NPerWmma) %
|
||||
ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_::At(I1) ==
|
||||
0,
|
||||
"wrong!");
|
||||
|
||||
constexpr index_t mreduce_per_thread =
|
||||
(CShuffleMRepeatPerShuffle * BlockwiseGemmPipe::MWaves * MPerWmma) /
|
||||
ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_::At(I0);
|
||||
|
||||
constexpr index_t nreduce_per_thread =
|
||||
(CShuffleNRepeatPerShuffle * BlockwiseGemmPipe::NWaves * NPerWmma) /
|
||||
ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_::At(I1);
|
||||
|
||||
static constexpr index_t NumReduce = ReduceTrait::ReducePtrsGlobal_::Size();
|
||||
|
||||
constexpr auto c_reduce_thread_lengths_mperblock_nperblock =
|
||||
Sequence<mreduce_per_thread, nreduce_per_thread>{};
|
||||
|
||||
// VGPR c_reduce_thread_desc_mperblock_nperblock
|
||||
constexpr auto c_reduce_thread_desc_mperblock_nperblock =
|
||||
make_naive_tensor_descriptor_packed(
|
||||
make_tuple(Number<mreduce_per_thread>{}, Number<nreduce_per_thread>{}));
|
||||
|
||||
// VGPR reduce_thread_desc_mperblock
|
||||
constexpr auto reduce_thread_desc_mperblock =
|
||||
make_naive_tensor_descriptor_packed(make_tuple(Number<mreduce_per_thread>{}));
|
||||
|
||||
// VGPR reduce_thread_desc_mblock_mperblock
|
||||
constexpr auto reduce_thread_desc_mblock_mperblock =
|
||||
make_naive_tensor_descriptor_packed(make_tuple(I1, Number<mreduce_per_thread>{}));
|
||||
|
||||
auto c_reduce_thread_buf =
|
||||
make_static_buffer<AddressSpaceEnum::Vgpr, typename ReduceTrait::ReduceAccDataType_>(
|
||||
c_reduce_thread_desc_mperblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
// reduce: threadwise copy from LDS to VGPR
|
||||
constexpr auto c_reduce_thread_cluster_desc = make_cluster_descriptor(
|
||||
typename ReduceTrait::CReduceThreadClusterLengths_MPerBlock_NPerBlock_{},
|
||||
Sequence<1, 0>{});
|
||||
|
||||
const auto c_reduce_thread_cluster_idx = c_reduce_thread_cluster_desc.CalculateBottomIndex(
|
||||
make_multi_index(get_thread_local_1d_id()));
|
||||
|
||||
const auto c_reduce_thread_data_idx_begin =
|
||||
c_reduce_thread_cluster_idx * c_reduce_thread_lengths_mperblock_nperblock;
|
||||
|
||||
auto c_reduce_thread_copy_lds_to_vgpr = ThreadwiseTensorSliceTransfer_v2<
|
||||
CShuffleDataType,
|
||||
typename ReduceTrait::ReduceAccDataType_,
|
||||
decltype(c_reduce_block_desc_mperblock_nperblock),
|
||||
decltype(c_reduce_thread_desc_mperblock_nperblock),
|
||||
decltype(c_reduce_thread_lengths_mperblock_nperblock),
|
||||
Sequence<0, 1>,
|
||||
1,
|
||||
ReduceTrait::CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock_,
|
||||
1,
|
||||
true>{c_reduce_block_desc_mperblock_nperblock, c_reduce_thread_data_idx_begin};
|
||||
|
||||
auto reduce_tuple_thread_copy_vgpr_to_global = generate_tuple(
|
||||
[&](auto I) {
|
||||
auto p_reduce_grid = p_reduces_grid[I];
|
||||
auto reduce_acc_element_op = reduce_out_element_ops[I];
|
||||
|
||||
return ThreadwiseTensorSliceTransfer_v1r3<
|
||||
typename ReduceTrait::ReduceAccDataType_,
|
||||
remove_pointer_t<decltype(p_reduce_grid)>,
|
||||
decltype(reduce_thread_desc_mblock_mperblock),
|
||||
decltype(reduce_grid_desc_mblock_mperblock),
|
||||
decltype(reduce_acc_element_op),
|
||||
Sequence<1, mreduce_per_thread>,
|
||||
Sequence<0, 1>,
|
||||
1,
|
||||
ReduceTrait::CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock_,
|
||||
ReduceTrait::ReduceGlobalMemoryDataOperation_::At(I),
|
||||
1,
|
||||
false>{reduce_grid_desc_mblock_mperblock,
|
||||
make_multi_index(block_m_id, // mblock
|
||||
c_reduce_thread_data_idx_begin[I0]), // mperblock
|
||||
reduce_acc_element_op};
|
||||
},
|
||||
Number<NumReduce>{});
|
||||
|
||||
constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
|
||||
|
||||
static_assert(num_access == sfc_cde_global.GetNumOfAccess(), "wrong!");
|
||||
|
||||
// CShuffle and Store
|
||||
static_for<0, num_access, 1>{}([&](auto access_id) {
|
||||
// make sure it's safe to write to LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each thread write its data from VGPR to LDS
|
||||
c_thread_copy_vgpr_to_lds.Run(
|
||||
c_thread_desc_mrepeat_mwave_msubgroup_nrepeat_nwave_nthreadpersubgroup_maccvgprs,
|
||||
sfc_c_vgpr.GetIndexTupleOfNumber(access_id),
|
||||
c_thread_buf,
|
||||
c_block_desc_mrepeat_mwave_msubgroup_nrepeat_nwave_nthreadpersubgroup_maccvgprs,
|
||||
c_shuffle_block_buf);
|
||||
|
||||
// make sure it's safe to read from LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each block loads its C data from LDS, D from global, applies elementwise
|
||||
// operation and stores result E to global
|
||||
cde_shuffle_block_copy_lds_and_global.Run(
|
||||
c_ds_desc_refs,
|
||||
c_ds_buf_refs,
|
||||
tie(e_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
tie(e_grid_buf));
|
||||
|
||||
{
|
||||
c_reduce_thread_copy_lds_to_vgpr.Run(c_reduce_block_desc_mperblock_nperblock,
|
||||
c_shuffle_block_buf,
|
||||
c_reduce_thread_desc_mperblock_nperblock,
|
||||
make_tuple(I0, I0),
|
||||
c_reduce_thread_buf);
|
||||
|
||||
static_for<0, NumReduce, 1>{}([&](auto In) {
|
||||
auto& p_reduce_grid = p_reduces_grid[In];
|
||||
|
||||
auto reduce_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
p_reduce_grid, reduce_grid_desc_mblock_mperblock.GetElementSpaceSize());
|
||||
|
||||
auto reduce_thread_buf =
|
||||
make_static_buffer<AddressSpaceEnum::Vgpr,
|
||||
typename ReduceTrait::ReduceAccDataType_>(
|
||||
reduce_thread_desc_mperblock.GetElementSpaceSize());
|
||||
|
||||
auto& reduce_in_element_op = reduce_in_element_ops[In];
|
||||
|
||||
auto& reduce_thread_copy_vgpr_to_global =
|
||||
reduce_tuple_thread_copy_vgpr_to_global(In);
|
||||
|
||||
using ReduceOperation =
|
||||
remove_cvref_t<decltype(typename ReduceTrait::ReduceOperations_{}[In])>;
|
||||
using ThreadwiseReduce =
|
||||
ThreadwiseReduction<typename ReduceTrait::ReduceAccDataType_,
|
||||
decltype(c_reduce_thread_desc_mperblock_nperblock),
|
||||
decltype(reduce_thread_desc_mperblock),
|
||||
ReduceOperation,
|
||||
false>;
|
||||
|
||||
// Global write Gemm shuffle + reduction
|
||||
const auto reduce_identityVal = ReduceOperation::template GetIdentityValue<
|
||||
typename ReduceTrait::ReduceAccDataType_>();
|
||||
|
||||
static_for<0, mreduce_per_thread, 1>{}(
|
||||
[&](auto I) { reduce_thread_buf(I) = reduce_identityVal; });
|
||||
|
||||
// reduce in VGPR
|
||||
static_for<0, mreduce_per_thread, 1>{}([&](auto im) {
|
||||
static_for<0, nreduce_per_thread, 1>{}([&](auto in) {
|
||||
constexpr auto offset =
|
||||
Number<c_reduce_thread_desc_mperblock_nperblock.CalculateOffset(
|
||||
make_tuple(im, in))>{};
|
||||
|
||||
reduce_in_element_op(c_reduce_thread_buf(offset),
|
||||
c_reduce_thread_buf(offset));
|
||||
});
|
||||
});
|
||||
|
||||
ThreadwiseReduce::Reduce(c_reduce_thread_buf, reduce_thread_buf);
|
||||
|
||||
// copy from VGPR to Global
|
||||
reduce_thread_copy_vgpr_to_global.Run(reduce_thread_desc_mblock_mperblock,
|
||||
make_tuple(I0, I0),
|
||||
reduce_thread_buf,
|
||||
reduce_grid_desc_mblock_mperblock,
|
||||
reduce_grid_buf);
|
||||
|
||||
if constexpr(access_id < num_access - 1)
|
||||
{
|
||||
constexpr auto c_global_step = sfc_cde_global.GetForwardStep(access_id);
|
||||
reduce_thread_copy_vgpr_to_global.MoveDstSliceWindow(
|
||||
reduce_grid_desc_mblock_mperblock,
|
||||
make_tuple(c_global_step[I0], c_global_step[I1]));
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
if constexpr(access_id < num_access - 1)
|
||||
{
|
||||
constexpr auto cde_global_step = sfc_cde_global.GetForwardStep(access_id);
|
||||
// move on Ds
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
cde_shuffle_block_copy_lds_and_global.MoveSrcSliceWindow(
|
||||
c_ds_desc_refs, i + I1, cde_global_step);
|
||||
});
|
||||
|
||||
// move on E
|
||||
cde_shuffle_block_copy_lds_and_global.MoveDstSliceWindow(
|
||||
tie(e_grid_desc_mblock_mperblock_nblock_nperblock), cde_global_step);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
typename ReduceTrait::ReducePtrsGlobal_ p_reduces_grid;
|
||||
typename ReduceTrait::ReduceInElementwiseOperations_ reduce_in_element_ops;
|
||||
typename ReduceTrait::ReduceAccElementwiseOperations_ reduce_out_element_ops;
|
||||
index_t MRaw;
|
||||
ReduceGridDesc_M reduce_grid_desc_m;
|
||||
};
|
||||
|
||||
} // namespace ck
|
||||
@@ -3,6 +3,7 @@
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
|
||||
#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v4r1.hpp"
|
||||
#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v7r3.hpp"
|
||||
|
||||
|
||||
@@ -25,6 +25,7 @@
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/epilogue_cshuffle_v3_wmma.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/epilogue_cshuffle_v3_welford_wmma.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/epilogue_cshuffle_v3_reduce_wmma.hpp"
|
||||
|
||||
namespace ck {
|
||||
|
||||
@@ -622,6 +623,29 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
BlockwiseGemmPipe,
|
||||
BlockSize>;
|
||||
|
||||
template <typename ReduceTrait>
|
||||
using EpilogueReduceCShuffle = EpilogueReduceCShuffle<
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
MPerWmma,
|
||||
NPerWmma,
|
||||
MRepeat,
|
||||
NRepeat,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
CDEElementwiseOperation,
|
||||
ThisThreadBlock,
|
||||
BlockwiseGemmPipe,
|
||||
GemmSpec,
|
||||
BlockSize,
|
||||
ReduceTrait>;
|
||||
|
||||
template <typename DEGridDesc>
|
||||
__device__ static constexpr auto MakeDEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
const DEGridDesc& de_grid_desc_m_n, index_t MBlock, index_t NBlock)
|
||||
|
||||
Reference in New Issue
Block a user