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Clone BlockwiseGemmXdlops_pipeline_v1 for WMMA implementation
This commit is contained in:
Anton Gorenko
@@ -0,0 +1,731 @@
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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 "ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_base.hpp"
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namespace ck {
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// Naive pipeline with lowest resource request per WGP
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// GlobalPrefetchStages: 1
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// LocalPreFillStages: 1
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// LocalPreFetchStages: 0
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// LocalSharedMemoryBuffer: 1
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template <BlockGemmPipelineScheduler BlkGemmPipelineVer,
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index_t BlockSize,
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typename ADataType,
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typename BDataType,
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typename ComputeDataType,
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typename AccDataType,
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typename ATileDesc,
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typename BTileDesc,
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typename AMmaTileDesc,
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typename BMmaTileDesc,
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index_t ABlockTransferSrcScalarPerVector,
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index_t BBlockTransferSrcScalarPerVector,
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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 MPerXDL,
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index_t NPerXDL,
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index_t MRepeat,
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index_t NRepeat,
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index_t KPacks>
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struct BlockwiseGemmXdlops_pipeline_v1
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{
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};
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template <index_t BlockSize,
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typename ADataType,
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typename BDataType,
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typename ComputeDataType,
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typename AccDataType,
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typename ATileDesc,
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typename BTileDesc,
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typename AMmaTileDesc,
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typename BMmaTileDesc,
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index_t ABlockTransferSrcScalarPerVector,
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index_t BBlockTransferSrcScalarPerVector,
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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 MPerXDL,
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index_t NPerXDL,
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index_t MRepeat,
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index_t NRepeat,
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index_t KPack
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// ,bool TransposeC //disable transposec right now...
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>
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struct BlockwiseGemmXdlops_pipeline_v1<BlockGemmPipelineScheduler::Intrawave,
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BlockSize,
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ADataType,
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BDataType,
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ComputeDataType,
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AccDataType,
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ATileDesc,
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BTileDesc,
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AMmaTileDesc,
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BMmaTileDesc,
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ABlockTransferSrcScalarPerVector,
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BBlockTransferSrcScalarPerVector,
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MPerBlock,
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NPerBlock,
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KPerBlock,
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MPerXDL,
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NPerXDL,
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MRepeat,
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NRepeat,
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KPack>
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: BlockwiseGemmXdlops_pipeline_base<BlockSize,
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ADataType,
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BDataType,
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ComputeDataType,
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AccDataType,
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ATileDesc,
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BTileDesc,
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AMmaTileDesc,
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BMmaTileDesc,
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ABlockTransferSrcScalarPerVector,
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BBlockTransferSrcScalarPerVector,
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MPerBlock,
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NPerBlock,
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KPerBlock,
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MPerXDL,
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NPerXDL,
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MRepeat,
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NRepeat,
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KPack>
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{
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using Base = BlockwiseGemmXdlops_pipeline_base<BlockSize,
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ADataType,
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BDataType,
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ComputeDataType,
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AccDataType,
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ATileDesc,
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BTileDesc,
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AMmaTileDesc,
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BMmaTileDesc,
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ABlockTransferSrcScalarPerVector,
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BBlockTransferSrcScalarPerVector,
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MPerBlock,
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NPerBlock,
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KPerBlock,
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MPerXDL,
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NPerXDL,
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MRepeat,
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NRepeat,
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KPack>;
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using Base::I0;
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using Base::KRepeat;
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using Base::xdlops_gemm;
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using Base::CalculateCThreadOriginDataIndex;
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using Base::CalculateCThreadOriginDataIndex8D;
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using Base::GetCBlockDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCBlockDescriptor_M0_N0_M1_N1_M2_N2_N3_N4;
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using Base::GetCThreadBuffer;
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using Base::GetCThreadDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCThreadDescriptor_M0_N0_M1_N1_M2_N2_N3_N4;
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using Base::MakeCGridDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::a_block_desc_m0_m1_m2_k;
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using Base::b_block_desc_n0_n1_n2_k;
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using Base::AMmaKStride;
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using Base::BMmaKStride;
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static constexpr index_t PrefetchStages = 1;
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static constexpr index_t PrefillStages = 1;
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static constexpr index_t GlobalBufferNum = 1;
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__host__ __device__ static constexpr bool BlockHasHotloop(index_t num_loop)
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{
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return num_loop > PrefetchStages;
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}
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__host__ __device__ static constexpr TailNumber BlockLoopTailNum(index_t num_loop)
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{
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ignore = num_loop;
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return TailNumber::Full;
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}
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template <bool HasMainLoop,
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TailNumber TailNum,
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typename AGridDesc,
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typename ABlockDesc,
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typename ABlockTransfer,
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typename AGridBuffer,
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typename ABlockBuffer,
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typename ABlockTransferStep,
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typename BGridDesc,
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typename BBlockDesc,
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typename BBlockTransfer,
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typename BGridBuffer,
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typename BBlockBuffer,
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typename BBlockTransferStep,
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typename CThreadBuffer>
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__device__ void Run(const AGridDesc& a_grid_desc,
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const ABlockDesc& a_block_desc,
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ABlockTransfer& a_blockwise_copy,
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const AGridBuffer& a_grid_buf,
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ABlockBuffer& a_block_buf,
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const ABlockTransferStep& a_block_copy_step,
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const BGridDesc& b_grid_desc,
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const BBlockDesc& b_block_desc,
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BBlockTransfer& b_blockwise_copy,
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const BGridBuffer& b_grid_buf,
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BBlockBuffer& b_block_buf,
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const BBlockTransferStep& b_block_copy_step,
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CThreadBuffer& c_thread_buf,
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index_t num_loop) const
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{
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auto a_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, ComputeDataType>(
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a_thread_desc_.GetElementSpaceSize());
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auto b_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, ComputeDataType>(
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b_thread_desc_.GetElementSpaceSize());
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// Global prefetch 1
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a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf);
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b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf);
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a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);
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b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);
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// Local prefill 1
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a_blockwise_copy.RunWrite(a_block_desc, a_block_buf);
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b_blockwise_copy.RunWrite(b_block_desc, b_block_buf);
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// Initialize C
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c_thread_buf.Clear();
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// main body
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if constexpr(HasMainLoop)
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{
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index_t i = 0;
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do
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{
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// -------------------------------------------------------------------------------------------
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a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf);
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b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf);
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a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);
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b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);
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block_sync_lds();
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static_for<0, KRepeat, 1>{}([&](auto k) {
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static_for<0, MRepeat, 1>{}([&](auto m0) {
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a_thread_copy_.Run(a_block_desc_m0_m1_m2_k,
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make_tuple(m0, I0, I0, Number<k * AMmaKStride>{}),
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a_block_buf,
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a_thread_desc_,
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make_tuple(m0, I0, k, I0),
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a_thread_buf);
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static_for<0, NRepeat, 1>{}([&](auto n0) {
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b_thread_copy_.Run(b_block_desc_n0_n1_n2_k,
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make_tuple(n0, I0, I0, Number<k * BMmaKStride>{}),
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b_block_buf,
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b_thread_desc_,
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make_tuple(n0, I0, k, I0),
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b_thread_buf);
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});
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});
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});
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static_for<0, KRepeat, 1>{}([&](auto k0) {
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static_for<0, MRepeat, 1>{}([&](auto m0) {
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static_for<0, NRepeat, 1>{}([&](auto n0) {
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vector_type<ComputeDataType, KPack> a_thread_vec;
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vector_type<ComputeDataType, KPack> b_thread_vec;
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static_for<0, KPack, 1>{}([&](auto ik) {
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a_thread_vec.template AsType<ComputeDataType>()(ik) =
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a_thread_buf[Number<a_thread_desc_.CalculateOffset(
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make_tuple(m0, I0, k0, ik))>{}];
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b_thread_vec.template AsType<ComputeDataType>()(ik) =
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b_thread_buf[Number<b_thread_desc_.CalculateOffset(
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make_tuple(n0, I0, k0, ik))>{}];
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});
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using mfma_input_type =
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typename vector_type<ComputeDataType,
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xdlops_gemm.K1PerXdlops>::type;
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constexpr index_t c_offset =
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c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));
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xdlops_gemm.Run(
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a_thread_vec.template AsType<mfma_input_type>(),
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b_thread_vec.template AsType<mfma_input_type>(),
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c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));
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});
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});
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});
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block_sync_lds();
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a_blockwise_copy.RunWrite(a_block_desc, a_block_buf);
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b_blockwise_copy.RunWrite(b_block_desc, b_block_buf);
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i += 1;
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} while(i < (num_loop - 1));
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}
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// tail
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if constexpr(TailNum == TailNumber::Full)
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{
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block_sync_lds();
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static_for<0, KRepeat, 1>{}([&](auto k) {
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static_for<0, MRepeat, 1>{}([&](auto m0) {
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a_thread_copy_.Run(a_block_desc_m0_m1_m2_k,
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make_tuple(m0, I0, I0, Number<k * AMmaKStride>{}),
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a_block_buf,
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a_thread_desc_,
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make_tuple(m0, I0, k, I0),
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a_thread_buf);
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static_for<0, NRepeat, 1>{}([&](auto n0) {
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b_thread_copy_.Run(b_block_desc_n0_n1_n2_k,
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make_tuple(n0, I0, I0, Number<k * BMmaKStride>{}),
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b_block_buf,
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b_thread_desc_,
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make_tuple(n0, I0, k, I0),
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b_thread_buf);
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});
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});
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});
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static_for<0, KRepeat, 1>{}([&](auto k0) {
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static_for<0, MRepeat, 1>{}([&](auto m0) {
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static_for<0, NRepeat, 1>{}([&](auto n0) {
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vector_type<ComputeDataType, KPack> a_thread_vec;
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vector_type<ComputeDataType, KPack> b_thread_vec;
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static_for<0, KPack, 1>{}([&](auto ik) {
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a_thread_vec.template AsType<ComputeDataType>()(ik) =
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a_thread_buf[Number<a_thread_desc_.CalculateOffset(
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make_tuple(m0, I0, k0, ik))>{}];
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b_thread_vec.template AsType<ComputeDataType>()(ik) =
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b_thread_buf[Number<b_thread_desc_.CalculateOffset(
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make_tuple(n0, I0, k0, ik))>{}];
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});
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using mfma_input_type =
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typename vector_type<ComputeDataType, xdlops_gemm.K1PerXdlops>::type;
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constexpr index_t c_offset =
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c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));
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xdlops_gemm.Run(a_thread_vec.template AsType<mfma_input_type>(),
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b_thread_vec.template AsType<mfma_input_type>(),
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c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));
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});
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});
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});
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}
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}
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protected:
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using Base::a_thread_copy_;
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using Base::a_thread_desc_;
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using Base::b_thread_copy_;
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using Base::b_thread_desc_;
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using Base::c_thread_desc_;
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};
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template <index_t BlockSize,
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typename ADataType,
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typename BDataType,
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typename ComputeDataType,
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typename AccDataType,
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typename ATileDesc,
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typename BTileDesc,
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typename AMmaTileDesc,
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typename BMmaTileDesc,
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index_t ABlockTransferSrcScalarPerVector,
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index_t BBlockTransferSrcScalarPerVector,
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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 MPerXDL,
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index_t NPerXDL,
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index_t MRepeat,
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index_t NRepeat,
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index_t KPack
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// ,bool TransposeC //disable transposec right now...
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>
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struct BlockwiseGemmXdlops_pipeline_v1<BlockGemmPipelineScheduler::Interwave,
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BlockSize,
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ADataType,
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BDataType,
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ComputeDataType,
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AccDataType,
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ATileDesc,
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BTileDesc,
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AMmaTileDesc,
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BMmaTileDesc,
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ABlockTransferSrcScalarPerVector,
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BBlockTransferSrcScalarPerVector,
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MPerBlock,
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NPerBlock,
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KPerBlock,
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MPerXDL,
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NPerXDL,
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MRepeat,
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NRepeat,
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KPack>
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: BlockwiseGemmXdlops_pipeline_base<BlockSize,
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ADataType,
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BDataType,
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ComputeDataType,
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AccDataType,
|
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ATileDesc,
|
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BTileDesc,
|
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AMmaTileDesc,
|
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BMmaTileDesc,
|
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ABlockTransferSrcScalarPerVector,
|
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BBlockTransferSrcScalarPerVector,
|
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MPerBlock,
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NPerBlock,
|
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KPerBlock,
|
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MPerXDL,
|
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NPerXDL,
|
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MRepeat,
|
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NRepeat,
|
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KPack>
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|
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{
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using Base = BlockwiseGemmXdlops_pipeline_base<BlockSize,
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ADataType,
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BDataType,
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ComputeDataType,
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AccDataType,
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ATileDesc,
|
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BTileDesc,
|
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AMmaTileDesc,
|
||||
BMmaTileDesc,
|
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ABlockTransferSrcScalarPerVector,
|
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BBlockTransferSrcScalarPerVector,
|
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MPerBlock,
|
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NPerBlock,
|
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KPerBlock,
|
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MPerXDL,
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NPerXDL,
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MRepeat,
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NRepeat,
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KPack>;
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using Base::A_K1;
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using Base::B_K1;
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using Base::I0;
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using Base::I1;
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using Base::KPerThread;
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using Base::xdlops_gemm;
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using Base::CalculateCThreadOriginDataIndex;
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using Base::CalculateCThreadOriginDataIndex8D;
|
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using Base::GetCBlockDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;
|
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using Base::GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCBlockDescriptor_M0_N0_M1_N1_M2_N2_N3_N4;
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using Base::GetCThreadBuffer;
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using Base::GetCThreadDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::GetCThreadDescriptor_M0_N0_M1_N1_M2_N2_N3_N4;
|
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using Base::MakeCGridDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;
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using Base::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;
|
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using Base::a_block_desc_m0_m1_m2_k;
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using Base::b_block_desc_n0_n1_n2_k;
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static constexpr index_t NumMacClusters = CK_EXPERIMENTAL_INTER_WAVE_SCHEDULING_MAC_CLUSTERS;
|
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static constexpr index_t KPerInnerLoop = math::max(KPerThread / NumMacClusters, KPack);
|
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static constexpr index_t KRepeat = KPerThread / KPerInnerLoop;
|
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static constexpr index_t PrefetchStages = 1;
|
||||
static constexpr index_t PrefillStages = 1;
|
||||
static constexpr index_t GlobalBufferNum = 1;
|
||||
__host__ __device__ static constexpr bool BlockHasHotloop(index_t num_loop)
|
||||
{
|
||||
return num_loop > PrefetchStages;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr TailNumber BlockLoopTailNum(index_t num_loop)
|
||||
{
|
||||
ignore = num_loop;
|
||||
return TailNumber::Full;
|
||||
}
|
||||
|
||||
template <bool HasMainLoop,
|
||||
TailNumber TailNum,
|
||||
typename AGridDesc,
|
||||
typename ABlockDesc,
|
||||
typename ABlockTransfer,
|
||||
typename AGridBuffer,
|
||||
typename ABlockBuffer,
|
||||
typename ABlockTransferStep,
|
||||
typename BGridDesc,
|
||||
typename BBlockDesc,
|
||||
typename BBlockTransfer,
|
||||
typename BGridBuffer,
|
||||
typename BBlockBuffer,
|
||||
typename BBlockTransferStep,
|
||||
typename CThreadBuffer>
|
||||
__device__ void Run(const AGridDesc& a_grid_desc,
|
||||
const ABlockDesc& a_block_desc,
|
||||
ABlockTransfer& a_blockwise_copy,
|
||||
const AGridBuffer& a_grid_buf,
|
||||
ABlockBuffer& a_block_buf,
|
||||
const ABlockTransferStep& a_block_copy_step,
|
||||
const BGridDesc& b_grid_desc,
|
||||
const BBlockDesc& b_block_desc,
|
||||
BBlockTransfer& b_blockwise_copy,
|
||||
const BGridBuffer& b_grid_buf,
|
||||
BBlockBuffer& b_block_buf,
|
||||
const BBlockTransferStep& b_block_copy_step,
|
||||
CThreadBuffer& c_thread_buf,
|
||||
index_t num_loop) const
|
||||
{
|
||||
auto a_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, ComputeDataType>(
|
||||
a_thread_desc_.GetElementSpaceSize());
|
||||
auto b_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, ComputeDataType>(
|
||||
b_thread_desc_.GetElementSpaceSize());
|
||||
|
||||
// Global prefetch 1
|
||||
a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf);
|
||||
b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf);
|
||||
|
||||
a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);
|
||||
b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);
|
||||
|
||||
// Local prefill 1
|
||||
a_blockwise_copy.RunWrite(a_block_desc, a_block_buf);
|
||||
b_blockwise_copy.RunWrite(b_block_desc, b_block_buf);
|
||||
|
||||
// Initialize C
|
||||
c_thread_buf.Clear();
|
||||
|
||||
// main body
|
||||
if constexpr(HasMainLoop)
|
||||
{
|
||||
index_t i = 0;
|
||||
do
|
||||
{
|
||||
// -------------------------------------------------------------------------------------------
|
||||
a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf);
|
||||
b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf);
|
||||
|
||||
a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);
|
||||
b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);
|
||||
|
||||
block_sync_lds();
|
||||
static_for<0, KRepeat, 1>{}([&](auto k0) {
|
||||
static_for<0, MRepeat, 1>{}([&](auto m0) {
|
||||
a_thread_copy_.Run(a_block_desc_m0_m1_m2_k,
|
||||
make_tuple(m0, I0, I0, Number<k0 * KPerInnerLoop>{}),
|
||||
a_block_buf,
|
||||
a_thread_desc_,
|
||||
make_tuple(m0, I0, k0, I0),
|
||||
a_thread_buf);
|
||||
static_for<0, NRepeat, 1>{}([&](auto n0) {
|
||||
b_thread_copy_.Run(b_block_desc_n0_n1_n2_k,
|
||||
make_tuple(n0, I0, I0, Number<k0 * KPerInnerLoop>{}),
|
||||
b_block_buf,
|
||||
b_thread_desc_,
|
||||
make_tuple(n0, I0, k0, I0),
|
||||
b_thread_buf);
|
||||
});
|
||||
});
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
// NOTE: Synchronize threads in a workgroup at the start of each MAC cluster,
|
||||
// but except the first, as we can shorten non-MAC cluster a bit and there's no
|
||||
// observable negative impact. The desired effect is waves in a workgroup
|
||||
// executing MAC in sync. This avoids some out-of-sync waves hijacking MAC
|
||||
// resource from other workgroups and reducing the chance of latency hiding by
|
||||
// waiting for the rest of the workgroup at the eventual sync point.
|
||||
if constexpr(k0.value != 0 || KRepeat == 1)
|
||||
{
|
||||
__builtin_amdgcn_s_barrier();
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
}
|
||||
static_for<0, KPerInnerLoop, KPack>{}([&](auto k_) {
|
||||
static_for<0, MRepeat, 1>{}([&](auto m0) {
|
||||
static_for<0, NRepeat, 1>{}([&](auto n0) {
|
||||
vector_type<ComputeDataType, KPack> a_thread_vec;
|
||||
vector_type<ComputeDataType, KPack> b_thread_vec;
|
||||
|
||||
static_for<0, KPack, 1>{}([&](auto ik) {
|
||||
a_thread_vec.template AsType<ComputeDataType>()(ik) =
|
||||
a_thread_buf[Number<a_thread_desc_.CalculateOffset(
|
||||
make_tuple(m0, I0, k0, k_ + ik))>{}];
|
||||
b_thread_vec.template AsType<ComputeDataType>()(ik) =
|
||||
b_thread_buf[Number<b_thread_desc_.CalculateOffset(
|
||||
make_tuple(n0, I0, k0, k_ + ik))>{}];
|
||||
});
|
||||
|
||||
using mfma_input_type =
|
||||
typename vector_type<ComputeDataType,
|
||||
xdlops_gemm.K1PerXdlops>::type;
|
||||
|
||||
constexpr index_t c_offset =
|
||||
c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));
|
||||
|
||||
// The block_sync_lds() here performs double duty:
|
||||
// A) safeguard against data hazard because barrier from
|
||||
// blockwise_gemm is moved here B) reduce VMEM FIFO congestion by
|
||||
// applying small delays to different wavefronts It is performed
|
||||
// near the end of MAC cluster to minimize lgkmcnt penalty
|
||||
if constexpr(k0.value == KRepeat - 1 &&
|
||||
k_.value == KPerInnerLoop - KPack &&
|
||||
m0.value == MRepeat - 1 && n0.value == NRepeat - 1)
|
||||
{
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
block_sync_lds();
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
}
|
||||
xdlops_gemm.Run(
|
||||
a_thread_vec.template AsType<mfma_input_type>(),
|
||||
b_thread_vec.template AsType<mfma_input_type>(),
|
||||
c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));
|
||||
if constexpr(k_.value == 0 && m0.value == 0 && n0.value == 0)
|
||||
{
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
__builtin_amdgcn_s_setprio(1);
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
}
|
||||
});
|
||||
});
|
||||
});
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
__builtin_amdgcn_s_setprio(0);
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
});
|
||||
|
||||
// block_sync_lds();
|
||||
a_blockwise_copy.RunWrite(a_block_desc, a_block_buf);
|
||||
b_blockwise_copy.RunWrite(b_block_desc, b_block_buf);
|
||||
|
||||
i += 1;
|
||||
} while(i < (num_loop - 1));
|
||||
}
|
||||
|
||||
// tail
|
||||
if constexpr(TailNum == TailNumber::Full)
|
||||
{
|
||||
block_sync_lds();
|
||||
static_for<0, KRepeat, 1>{}([&](auto k0) {
|
||||
static_for<0, MRepeat, 1>{}([&](auto m0) {
|
||||
a_thread_copy_.Run(a_block_desc_m0_m1_m2_k,
|
||||
make_tuple(m0, I0, I0, Number<k0 * KPerInnerLoop>{}),
|
||||
a_block_buf,
|
||||
a_thread_desc_,
|
||||
make_tuple(m0, I0, k0, I0),
|
||||
a_thread_buf);
|
||||
static_for<0, NRepeat, 1>{}([&](auto n0) {
|
||||
b_thread_copy_.Run(b_block_desc_n0_n1_n2_k,
|
||||
make_tuple(n0, I0, I0, Number<k0 * KPerInnerLoop>{}),
|
||||
b_block_buf,
|
||||
b_thread_desc_,
|
||||
make_tuple(n0, I0, k0, I0),
|
||||
b_thread_buf);
|
||||
});
|
||||
});
|
||||
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
if constexpr(k0.value != 0 || KRepeat == 1)
|
||||
{
|
||||
__builtin_amdgcn_s_barrier();
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
}
|
||||
static_for<0, KPerInnerLoop, KPack>{}([&](auto k_) {
|
||||
static_for<0, MRepeat, 1>{}([&](auto m0) {
|
||||
static_for<0, NRepeat, 1>{}([&](auto n0) {
|
||||
vector_type<ComputeDataType, KPack> a_thread_vec;
|
||||
vector_type<ComputeDataType, KPack> b_thread_vec;
|
||||
|
||||
static_for<0, KPack, 1>{}([&](auto ik) {
|
||||
a_thread_vec.template AsType<ComputeDataType>()(ik) =
|
||||
a_thread_buf[Number<a_thread_desc_.CalculateOffset(
|
||||
make_tuple(m0, I0, k0, k_ + ik))>{}];
|
||||
b_thread_vec.template AsType<ComputeDataType>()(ik) =
|
||||
b_thread_buf[Number<b_thread_desc_.CalculateOffset(
|
||||
make_tuple(n0, I0, k0, k_ + ik))>{}];
|
||||
});
|
||||
|
||||
using mfma_input_type =
|
||||
typename vector_type<ComputeDataType,
|
||||
xdlops_gemm.K1PerXdlops>::type;
|
||||
|
||||
constexpr index_t c_offset =
|
||||
c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));
|
||||
|
||||
if constexpr(k0.value == KRepeat - 1 &&
|
||||
k_.value == KPerInnerLoop - KPack &&
|
||||
m0.value == MRepeat - 1 && n0.value == NRepeat - 1)
|
||||
{
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
block_sync_lds();
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
}
|
||||
xdlops_gemm.Run(
|
||||
a_thread_vec.template AsType<mfma_input_type>(),
|
||||
b_thread_vec.template AsType<mfma_input_type>(),
|
||||
c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));
|
||||
if constexpr(k_.value == 0 && m0.value == 0 && n0.value == 0)
|
||||
{
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
__builtin_amdgcn_s_setprio(1);
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
}
|
||||
});
|
||||
});
|
||||
});
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
__builtin_amdgcn_s_setprio(0);
|
||||
__builtin_amdgcn_sched_barrier(0);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
protected:
|
||||
// K->M loopover
|
||||
static constexpr auto a_thread_desc_ = make_naive_tensor_descriptor(
|
||||
make_tuple(Number<MRepeat>{}, I1, Number<KRepeat>{}, Number<KPerInnerLoop>{}),
|
||||
make_tuple(Number<KPerInnerLoop>{},
|
||||
Number<KRepeat * MRepeat * KPerInnerLoop>{},
|
||||
Number<MRepeat * KPerInnerLoop>{},
|
||||
I1));
|
||||
|
||||
static constexpr auto b_thread_desc_ = make_naive_tensor_descriptor(
|
||||
make_tuple(Number<NRepeat>{}, I1, Number<KRepeat>{}, Number<KPerInnerLoop>{}),
|
||||
make_tuple(Number<KPerInnerLoop>{},
|
||||
Number<KRepeat * NRepeat * KPerInnerLoop>{},
|
||||
Number<NRepeat * KPerInnerLoop>{},
|
||||
I1));
|
||||
|
||||
using AThreadCopy = ThreadwiseTensorSliceTransfer_v4<ADataType,
|
||||
ComputeDataType,
|
||||
decltype(a_block_desc_m0_m1_m2_k),
|
||||
decltype(a_thread_desc_),
|
||||
Sequence<1, 1, 1, KPerInnerLoop>,
|
||||
Sequence<0, 1, 2, 3>,
|
||||
3,
|
||||
A_K1,
|
||||
A_K1>;
|
||||
|
||||
using BThreadCopy = ThreadwiseTensorSliceTransfer_v4<BDataType,
|
||||
ComputeDataType,
|
||||
decltype(b_block_desc_n0_n1_n2_k),
|
||||
decltype(b_thread_desc_),
|
||||
Sequence<1, 1, 1, KPerInnerLoop>,
|
||||
Sequence<0, 1, 2, 3>,
|
||||
3,
|
||||
B_K1,
|
||||
B_K1>;
|
||||
|
||||
AThreadCopy a_thread_copy_{Base::CalculateAThreadOriginDataIndex()};
|
||||
BThreadCopy b_thread_copy_{Base::CalculateBThreadOriginDataIndex()};
|
||||
using Base::c_thread_desc_;
|
||||
};
|
||||
|
||||
} // namespace ck
|
||||
Reference in New Issue
Block a user