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https://github.com/ROCm/composable_kernel.git
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aa932445ea
* Add a gpu gemm reference kernel * Switch to gpu reference in gemm examples * Remove redundant arguments * Update all related examples * Update more examples * Try less threads per block * Try even less threads per block * Add support for all matrix layouts * Increase block size * Clean up * Remove hardcoded strides * Clean up * Try a column-major case * Revert back to row-major * Run both CPU and GPU veriffication --------- Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
61 lines
5.5 KiB
C++
61 lines
5.5 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
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#include "common.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle.hpp"
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using ADataType = ck::f8_t;
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using BDataType = ck::bf8_t;
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using CDataType = ck::half_t;
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using AccDataType = float;
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using CShuffleDataType = float;
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using ALayout = Row;
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using BLayout = Col;
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using CLayout = Row;
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using AElementOp = PassThrough;
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using BElementOp = PassThrough;
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using CElementOp = PassThrough;
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static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
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static constexpr auto LoopSched = ck::make_default_loop_scheduler();
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static constexpr auto PipelineVer = ck::PipelineVersion::v1;
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using ComputeTypeA = ck::f8_t;
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using ComputeTypeB = ck::bf8_t;
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// clang-format off
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using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
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// ######| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer| Loop| Pipeline| Compute| Compute|
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// ######| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector| Scheduler| Version| TypeA| TypeB|
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// ######| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl| | | | |
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// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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< ALayout, BLayout, CLayout, ADataType, BDataType, CDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CElementOp, GemmDefault, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, 8, LoopSched, PipelineVer, ComputeTypeA, ComputeTypeB>;
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// clang-format on
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using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataType,
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BDataType,
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CDataType,
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AccDataType,
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AElementOp,
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BElementOp,
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CElementOp,
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ComputeTypeA,
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ComputeTypeB>;
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using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
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BLayout,
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CLayout,
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ADataType,
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BDataType,
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CDataType,
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AccDataType,
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AElementOp,
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BElementOp,
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CElementOp>;
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#include "run_gemm_example.inc"
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int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
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