mirror of
https://github.com/ROCm/composable_kernel.git
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Wmma support for multiple Ds based GEMMs (#2613)
* Fixed cmake errors related to gemm_bilinear. Previously, if the above flags are set, cmake build fails: GPU_TARGETS="gfx1100;gfx1201" -D DTYPES="fp16;bf16;fp8" * Fixed cmake build errors related to test_fp8 * Updates to support mixed precision (cherry picked from commit e65d71180393e7b66169c56565a6bac740427de6) Co-authored-by: Anca Hamuraru <anca@streamhpc.com> * Adding support for RRR, F8xF16xF16 gemm_universal_wmma - wip (cherry picked from commit f8c06322df0abcbd5945a56cdf5bffe56480f9f0) Co-authored-by: Anca Hamuraru <anca@streamhpc.com> * Added support for F8xF16xF16 to gemm_wmma_universal (cherry picked from commit 15c851de6daa513a12c2e3af299bab0176175fb5) Co-authored-by: Anca Hamuraru <anca@streamhpc.com> * Added support for F16xF8xF16 to gemm_wmma_universal * Added support for BF16xI4xBF16 to gemm_wmma_universal (cherry picked from commit c6a4a69d2d43d59bae8bdabfae80d648646f217e) Co-authored-by: Anca Hamuraru <anca@streamhpc.com> * Added support for F16xI4xF16 to gemm_wmma_universal * Fixed IsSupportedArgument to check ComputeTypeA, ComputeTypeB instead of ADataType, BDataType * Added missing test class for FP16_KM_NK * Pre-commit hooks fixes * Added padding instances for f16xf16xf16 * Fixed cmake errors related to gemm_bilinear. Previously, if the above flags are set, cmake build fails: GPU_TARGETS="gfx1100;gfx1201" -D DTYPES="fp16;bf16;fp8" (cherry picked from commit5bdc993dbf) Co-authored-by: Anca Hamuraru <anca@streamhpc.com> * Fixed cmake build errors related to test_fp8 (cherry picked from commit12176616b6) Co-authored-by: Anca Hamuraru <anca@streamhpc.com> * Ammending changes for adding support for padding instances for f16xf16xf16 * Fixes for padding instances for f16xf16xf16 * Added padding instances for bf16xbf16, f8xf8 * Added packed instances for bf16xi4xbf16 * Added padding instances for f8xf16xf16 * Added padding instances for f16xf8xf16, f16xi4xf16 * Fixed typos for bf16xbf16xbf16 padding instances * Fixed typos for padded instances * Added tests for fp16, KM_KN and KM_NK * Padding not supported for when BDataType is pk_i4_t. Added fix for correct check and removed padding instances. * Fixed typos * Updated the set of tests for FP16 * Updated the set of tests for FP16 * Fix typo * Moved f16xi4 test under the correct data layout group * example for gemm_universal_bf16 * Adding examples for gemm_wmma instances * Added the missing parameters * Fixed review comments and added executable to cmakeLists * Fixing clang format * Fixing build erros * Fixed compilation failure. * Modified some code as per gemm_universal_examples * Fixed the gemm specialization error * Fixed the build errors. * Fix strides of a/b_thread_desc The descriptors are larger than needed (even though the compiler don't alloc registers for unused values). * Load in M/NRepeat dims with thread copy's slice instead of a loop * Clone BlockwiseGemmXdlops_pipeline_v1 for WMMA implementation * Implement Intrawave and Interwave variants of pipeline v1 * Add instances for Interwave and Intrawave v1 * Add instances with ABlockLdsExtraM and BBlockLdsExtraN = 0 * Remove instances that are too slow (mostly because of register spilling) * Add a workaround for fp8/bf8->f32 packed conversion issue * Add instances for Interwave and Intrawave v1 * Enable profiling of mixed precision with f8 and int4 on WMMA * Fix segfault in profiler when B is pk_i4_t b_device_buf's size in bytes is larger than b_k_n_permute so b_device_buf.ToDevice reads out-of-bounds. * Remove instances that are too slow (mostly because of register spilling) * Add missing add_device_gemm_wmma_universal_f8_f8_bf16 declarations * Add test case for bf16_i4 * Add missing Regular tests * Add test_gemm_universal_xdl/wmma_fp16 to REGRESSION_TESTS They take more than 30 seconds * Fix a bug that fp16_i4 validation passes only with PermuteB A permutation required by conversion from pk_i4_t to half_t does not depend on PermuteB, they can be used independently. * Use PermuteB with f16_i4 in most instances (as xdl) Some instances use PermuteB = false for checking correctness. See also the previous commit. * Fix cache flushing for pk_i4 * Add mixed precision examples * Disable all tests and instances with f8 on gfx11 Even though f8_f16 and f16_f8 don't require f8 WMMA instructions, gfx11 still lacks hardware instructions for fast f8->f32 conversion. * Add FP16 KM_NK and KM_KN test suites for XDL These tests were added to common .inc for better testing of WMMA instances * Support multiple D in GridwiseGemm_wmma_cshuffle_v3 DeviceGemm_Wmma_CShuffleV3 is changed for new template parameters. * Use ThreadGroupTensorSliceTransfer_v7r3 * Clone for device_gemm_wmma_cshuffle_v3.hpp for future Multiple D support * Clone example/65_gemm_multiply_multiply/gemm_add_add_xdl_fp16.cpp for wmma * Implement DeviceGemmMultipleD_Wmma_CShuffleV3 * Make gemm_add_add_wmma to work with DeviceGemmMultipleD_Wmma_CShuffleV3 * Prepare gemma_add tests for adding wmma * Add gemm_add_fastgelu instances and test * Add a special wrapper to use DeviceGemmMultipleD_Wmma_CShuffleV3 with old API ckProfiler uses DeviceGemmMultipleD (tests also call its functions), the wrapper allows to use DeviceGemmMultipleDSplitK instances there. * removed unnecessary ck parts from compilation * initial gemm_add_multiply instance implementations * fixed profiler help message for gemm_add_multiply * improved multiply_add profiler layout help * fixed template arguments for test instances * added test for gemm_add_multiply * Support multiple D in GridwiseGemm_wmma_cshuffle_v3 DeviceGemm_Wmma_CShuffleV3 is changed for new template parameters. * Use ThreadGroupTensorSliceTransfer_v7r3 * Clone for device_gemm_wmma_cshuffle_v3.hpp for future Multiple D support * Clone example/65_gemm_multiply_multiply/gemm_add_add_xdl_fp16.cpp for wmma * Implement DeviceGemmMultipleD_Wmma_CShuffleV3 * Make gemm_add_add_wmma to work with DeviceGemmMultipleD_Wmma_CShuffleV3 * Prepare gemma_add tests for adding wmma * Add gemm_add_fastgelu instances and test * Add a special wrapper to use DeviceGemmMultipleD_Wmma_CShuffleV3 with old API ckProfiler uses DeviceGemmMultipleD (tests also call its functions), the wrapper allows to use DeviceGemmMultipleDSplitK instances there. * switched to splitK interface * log print added to splitk benchmarks * revert main cmake comments * newline change reverted * added add_fastgelu instances * revert unintended change in xdl add_fastgelu * created gemm_add_add_fastgelu instances * created fastegelu instances * added tests for all splitk fastgelus * Added tests. * multiply_add instances created * updates to add_multiply splitk instances * splitk xdl test fixes * added wmma multiply_multiply instances * fixed ONLY_XDL_AND_WMMA_KERNELS tag * Added gemm_add examples for wmma v1 and v3 * fixed / workarounded i8 instances * Modified the v3 code to added one fp16 bxdl instance. * added bf16 xdl instance. * adding gemm_add wmma_cshuffle and other support (cherry picked from commit ec447e7f564095ea969eddc39ec77b843aa52976) Co-authored-by: Cenxuan <cenxuan@streamhpc.com> * add instances into camkelists (cherry picked from commit 23bf2d2771c939ea3ca7f493433c55255bffd08e) Co-authored-by: Cenxuan <cenxuan@streamhpc.com> * This is work in progress, edited the template parameters in order to build (cherry picked from commit b4fde8a3314cb44659c4bbda35f1a0133c63dc41) Co-authored-by: Cenxuan <cenxuan@streamhpc.com> * temp work saved, changed the BDataType to f16 or bf16 since wmma currently not support non-equal A and B datatype (cherry picked from commit 22fbd68f1db458ab50780a394ee2544c7a1484d1) Co-authored-by: Cenxuan <cenxuan@streamhpc.com> * added datatype and use clang-format-12 (cherry picked from commit ae4e853682ef1bb27784b2f965b4a66b3751ceec) Co-authored-by: Cenxuan <cenxuan@streamhpc.com> * Fixing build errors * Added instances for v3 * Adding instances and executables * Code update of template parameters modified. * Renamed file. * Added tests. * resolved error tests. * Fixing build errors * Updated comments * removed the changes as per the MR review comment. * Updated tests. * fp8 instances - not tested * Restored the Cmake file that was reverted by mistake during rebase. * fixed wmma_op test * Updated comments. * Updated the template parameter description * fixed rdna4 instances * fixed back compatibility on gfx11 * cleanups * fix ckProfiler * one more cmake fix * added fp8 instances * Updated tests to ad BF16 instances as per review comment * Added include file and cleaned up(as per review comment) * Updated and optimized the example code for all types. * Fixed clang format * Resolve "Implement `device_gemm_bilinear` for RDNA4" * test generalization to handle FP16 shuffle better * added missing changes * Added bf16 wmma instance for add_relu * Added f16 wmma instance and corrected bf16 instance errors. * Added instances to Cmake * Modified the template parameters to make the instances work. * Fixed typo in profiler * Added v3 instances for gemm_add_relu * addressed core review comments * Added test for gemm_add_relu wmma instance * Cleaned up the code. * Added examples for gemm_add_relu * Fixing typo to resolve build errors. * Fixes applied to fix the precision loss. * fix billinear test after merge * Removed the old wmma instances. * Added wrapper and renamed the wmma_v3 instances * Updated copyrights and added wrappers. * Fixes applied according to review comments * Apply 1 suggestion(s) to 1 file(s) Co-authored-by: Robin Voetter <robin@streamhpc.com> * Removed the old wmma instances. * Updated wrapper for the v3 instances * removed the old wmma examples * Renamed the v3 instances * Deleted the gtest file added by mistake. * Updated thge profiler with wrapper * Fixed test errors. * Fixed the review comments * Fixed the if condition MACROS. * REVERTED THE PROFILER CHANGES * Revert "REVERTED THE PROFILER CHANGES" This reverts commit21cb98546c. * Revert "Fixed test errors." This reverts commit13efcc6fe1. * Revert "Updated thge profiler with wrapper" This reverts commit536f86661d. * Added missing wrapper instances * Updated copyrights. * Fixed typo. * Fixed copyrights. * Updated copyrights. * updated copyrights. * comments on the atomics workaround * fixed cmake comment * Fix bug from merge * clang-format-18 * Fix compilation error * Fix linking error * Fix bug in add and add_relu examples * Fix error including file (typo) * Quick fix to compile examples for different targets * Fix for multi target * implemented f16 and bf16 instances for gemm_silu * addressed review comments * addressed review comments * Fix clang format * Fix clang format --------- Co-authored-by: Anca Hamuraru <anca@streamhpc.com> Co-authored-by: apoorva <apoorva@streamhpc.com> Co-authored-by: Anton Gorenko <anton@streamhpc.com> Co-authored-by: Zoltan Lakatos <zoltan.lakatos@streamhpc.com> Co-authored-by: Cenxuan <cenxuan@streamhpc.com> Co-authored-by: Robin Voetter <robin@streamhpc.com> Co-authored-by: Kiefer van Teutem <kiefer.van.teutem@streamhpc.com> Co-authored-by: Kevin Abraham <kevin.abraham@streamhpc.com> Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com> [ROCm/composable_kernel commit:b740380906]
This commit is contained in:
Enrico Degregori
@@ -70,3 +70,5 @@ example_compile_options(example_gemm_multiply_multiply_xdl_fp8_blockscale_bpresh
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example_compile_options(example_moe_gemm2_xdl_fp8_blockscale PRIVATE ${BLOCKSCALE_GEMM_OPTIONS})
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example_compile_options(example_moe_gemm1_xdl_fp8_blockscale PRIVATE ${BLOCKSCALE_GEMM_OPTIONS})
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add_example_executable(example_gemm_add_add_wmma_fp16 gemm_add_add_wmma_fp16.cpp)
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267
example/65_gemm_multiply_multiply/gemm_add_add_wmma_fp16.cpp
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267
example/65_gemm_multiply_multiply/gemm_add_add_wmma_fp16.cpp
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@@ -0,0 +1,267 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
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#include <iostream>
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#include <numeric>
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#include <initializer_list>
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#include <cstdlib>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp"
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#include "ck/library/utility/device_memory.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/library/utility/host_tensor_generator.hpp"
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#include "ck/library/utility/literals.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/utility/blkgemmpipe_scheduler.hpp"
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template <ck::index_t... Is>
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using S = ck::Sequence<Is...>;
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using F16 = ck::half_t;
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using F32 = float;
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using Row = ck::tensor_layout::gemm::RowMajor;
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using Col = ck::tensor_layout::gemm::ColumnMajor;
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using A0DataType = F16;
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using B0DataType = F16;
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using AccDataType = F32;
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using CShuffleDataType = F32;
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using D0DataType = F32;
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using D1DataType = F32;
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using DsDataType = ck::Tuple<D0DataType, D1DataType>;
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using EDataType = F16;
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using A0Layout = Row;
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using B0Layout = Col;
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using D0Layout = Row;
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using D1Layout = Row;
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using DsLayout = ck::Tuple<D0Layout, D1Layout>;
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using ELayout = Row;
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struct AddAdd
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{
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template <typename E, typename C, typename D0, typename D1>
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__host__ __device__ constexpr void
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operator()(E& e, const C& c, const D0& d0, const D1& d1) const;
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template <>
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__host__ __device__ constexpr void operator()<ck::half_t, float, float, float>(
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ck::half_t& e, const float& c, const float& d0, const float& d1) const
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{
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const float x0_f = c + d0 + d1;
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e = ck::type_convert<ck::half_t>(x0_f);
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}
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};
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using AElementOp = PassThrough;
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using BElementOp = PassThrough;
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using CDEElementOp = AddAdd;
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static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::Default;
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using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultipleD_Wmma_CShuffleV3
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// clang-format off
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//#########################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
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//#########################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
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//#########################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
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//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| S<C, D..>| | |
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< A0Layout, B0Layout, DsLayout, ELayout, A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, ck::BlockGemmPipelineScheduler::Interwave, ck::BlockGemmPipelineVersion::v1>;
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// clang-format on
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int main(int argc, char* argv[])
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{
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bool do_verification = true;
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int init_method = 1;
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bool time_kernel = false;
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// GEMM shape
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ck::index_t M = 3840;
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ck::index_t N = 4096;
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ck::index_t K = 4096;
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ck::index_t StrideA = K;
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ck::index_t StrideB = K;
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ck::index_t StrideD = K;
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ck::index_t StrideE = N;
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if(argc == 1)
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{
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// use default case
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}
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else if(argc == 4)
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{
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do_verification = std::stoi(argv[1]);
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init_method = std::stoi(argv[2]);
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time_kernel = std::stoi(argv[3]);
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}
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else if(argc == 11)
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{
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do_verification = std::stoi(argv[1]);
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init_method = std::stoi(argv[2]);
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time_kernel = std::stoi(argv[3]);
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M = std::stoi(argv[4]);
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N = std::stoi(argv[5]);
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K = std::stoi(argv[6]);
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StrideA = std::stoi(argv[7]);
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StrideB = std::stoi(argv[8]);
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StrideD = std::stoi(argv[9]);
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StrideE = std::stoi(argv[10]);
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}
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else
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{
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printf("arg1: verification (0=no, 1=yes)\n");
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printf("arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n");
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printf("arg3: time kernel (0=no, 1=yes)\n");
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printf("arg4 to 9: M (256x), N(128x), K(32x), StrideA, StrideB, StrideD, StrideE\n");
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exit(0);
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}
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auto f_host_tensor_descriptor =
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[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
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using namespace ck::literals;
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if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
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{
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return HostTensorDescriptor({row, col}, {stride, 1_uz});
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}
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else
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{
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return HostTensorDescriptor({row, col}, {1_uz, stride});
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}
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};
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Tensor<A0DataType> a0_m_k(f_host_tensor_descriptor(M, K, StrideA, A0Layout{}));
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Tensor<B0DataType> b0_k_n(f_host_tensor_descriptor(K, N, StrideB, B0Layout{}));
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Tensor<D0DataType> d0_m_n(f_host_tensor_descriptor(M, N, StrideD, D0Layout{}));
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Tensor<D1DataType> d1_m_n(f_host_tensor_descriptor(M, N, StrideD, D1Layout{}));
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Tensor<EDataType> e_m_n_host_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
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Tensor<EDataType> e_m_n_device_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
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std::cout << "a0_m_k: " << a0_m_k.mDesc << std::endl;
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std::cout << "b0_k_n: " << b0_k_n.mDesc << std::endl;
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std::cout << "d1_m_n: " << d1_m_n.mDesc << std::endl;
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std::cout << "d0_m_n: " << d0_m_n.mDesc << std::endl;
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std::cout << "e_m_n: " << e_m_n_host_result.mDesc << std::endl;
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switch(init_method)
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{
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case 0: break;
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case 1:
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a0_m_k.GenerateTensorValue(GeneratorTensor_2<A0DataType>{-2, 2});
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b0_k_n.GenerateTensorValue(GeneratorTensor_2<B0DataType>{0, 2});
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d0_m_n.GenerateTensorValue(GeneratorTensor_2<D0DataType>{0, 2});
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d1_m_n.GenerateTensorValue(GeneratorTensor_2<D1DataType>{0, 2});
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break;
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default:
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a0_m_k.GenerateTensorValue(GeneratorTensor_3<A0DataType>{0.0, 1.0});
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b0_k_n.GenerateTensorValue(GeneratorTensor_3<B0DataType>{-0.5, 0.5});
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d0_m_n.GenerateTensorValue(GeneratorTensor_3<D0DataType>{-0.5, 0.5});
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d1_m_n.GenerateTensorValue(GeneratorTensor_3<D1DataType>{-0.5, 0.5});
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}
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DeviceMem a0_device_buf(sizeof(A0DataType) * a0_m_k.mDesc.GetElementSpaceSize());
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DeviceMem b0_device_buf(sizeof(B0DataType) * b0_k_n.mDesc.GetElementSpaceSize());
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DeviceMem d0_device_buf(sizeof(D0DataType) * d0_m_n.mDesc.GetElementSpaceSize());
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DeviceMem d1_device_buf(sizeof(D1DataType) * d1_m_n.mDesc.GetElementSpaceSize());
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DeviceMem e_device_buf(sizeof(EDataType) * e_m_n_device_result.mDesc.GetElementSpaceSize());
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a0_device_buf.ToDevice(a0_m_k.mData.data());
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b0_device_buf.ToDevice(b0_k_n.mData.data());
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d0_device_buf.ToDevice(d0_m_n.mData.data());
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d1_device_buf.ToDevice(d1_m_n.mData.data());
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auto a_element_op = AElementOp{};
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auto b_element_op = BElementOp{};
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auto cde_element_op = CDEElementOp{};
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constexpr ck::index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
// do GEMM
|
||||
auto device_op = DeviceOpInstance{};
|
||||
auto invoker = device_op.MakeInvoker();
|
||||
auto argument =
|
||||
device_op.MakeArgument(a0_device_buf.GetDeviceBuffer(),
|
||||
b0_device_buf.GetDeviceBuffer(),
|
||||
std::array<const void*, NumDTensor>{d0_device_buf.GetDeviceBuffer(),
|
||||
d1_device_buf.GetDeviceBuffer()},
|
||||
e_device_buf.GetDeviceBuffer(),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<ck::index_t, NumDTensor>{StrideD, StrideD},
|
||||
StrideE,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
|
||||
if(!device_op.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! device_gemm with the specified compilation parameters does "
|
||||
"not support this GEMM problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel, 0, 20, 50});
|
||||
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype = sizeof(A0DataType) * M * K + sizeof(B0DataType) * K * N +
|
||||
sizeof(D0DataType) * M * N + sizeof(D1DataType) * M * N +
|
||||
sizeof(EDataType) * M * N;
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< std::endl;
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
Tensor<CShuffleDataType> c_m_n({M, N});
|
||||
|
||||
using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<A0DataType,
|
||||
B0DataType,
|
||||
CShuffleDataType,
|
||||
AccDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
PassThrough>;
|
||||
auto ref_gemm = ReferenceGemmInstance{};
|
||||
auto ref_invoker = ref_gemm.MakeInvoker();
|
||||
|
||||
auto ref_argument = ref_gemm.MakeArgument(
|
||||
a0_m_k, b0_k_n, c_m_n, PassThrough{}, PassThrough{}, PassThrough{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
for(int m = 0; m < M; ++m)
|
||||
{
|
||||
for(int n = 0; n < N; ++n)
|
||||
{
|
||||
cde_element_op(e_m_n_host_result(m, n), c_m_n(m, n), d0_m_n(m, n), d1_m_n(m, n));
|
||||
}
|
||||
}
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
return ck::utils::check_err(e_m_n_device_result, e_m_n_host_result) ? 0 : 1;
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
@@ -184,7 +184,6 @@ int main(int argc, char* argv[])
|
||||
b0_device_buf.ToDevice(b0_k_n.mData.data());
|
||||
d0_device_buf.ToDevice(d0_m_n.mData.data());
|
||||
d1_device_buf.ToDevice(d1_m_n.mData.data());
|
||||
e_device_buf.ToDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
auto a_element_op = AElementOp{};
|
||||
auto b_element_op = BElementOp{};
|
||||
@@ -220,11 +219,12 @@ int main(int argc, char* argv[])
|
||||
"not support this GEMM problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel, 20, 50});
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel, 0, 20, 50});
|
||||
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype =
|
||||
sizeof(A0DataType) * M * K + sizeof(B0DataType) * K * N + sizeof(EDataType) * M * N;
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype = sizeof(A0DataType) * M * K + sizeof(B0DataType) * K * N +
|
||||
sizeof(D0DataType) * M * N + sizeof(D1DataType) * M * N +
|
||||
sizeof(EDataType) * M * N;
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
@@ -233,8 +233,6 @@ int main(int argc, char* argv[])
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< std::endl;
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
Tensor<CShuffleDataType> c_m_n({M, N});
|
||||
|
||||
22
example/68_gemm_add/CMakeLists.txt
Normal file
22
example/68_gemm_add/CMakeLists.txt
Normal file
@@ -0,0 +1,22 @@
|
||||
add_custom_target(example_gemm_add_xdl)
|
||||
|
||||
add_example_executable(example_gemm_add_xdl_fp16 gemm_add_xdl_fp16.cpp)
|
||||
add_example_dependencies(example_gemm_add_xdl example_gemm_add_xdl_fp16)
|
||||
|
||||
|
||||
add_example_executable(example_gemm_add_xdl_bf16 gemm_add_xdl_bf16.cpp)
|
||||
add_example_dependencies(example_gemm_add_xdl example_gemm_add_xdl_bf16)
|
||||
|
||||
add_custom_target(example_gemm_add_wmma)
|
||||
|
||||
add_example_executable(example_gemm_add_wmma_bf16 gemm_add_wmma_bf16.cpp)
|
||||
add_example_dependencies(example_gemm_add_wmma example_gemm_add_wmma_bf16)
|
||||
|
||||
add_example_executable(example_gemm_add_wmma_fp16 gemm_add_wmma_fp16.cpp)
|
||||
add_example_dependencies(example_gemm_add_wmma example_gemm_add_wmma_fp16)
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
114
example/68_gemm_add/common.hpp
Normal file
114
example/68_gemm_add/common.hpp
Normal file
@@ -0,0 +1,114 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <algorithm>
|
||||
#include <cstddef>
|
||||
#include <iostream>
|
||||
#include <stdexcept>
|
||||
#include <string>
|
||||
|
||||
#include "ck/ck.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
#include "ck/utility/data_type.hpp"
|
||||
|
||||
#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
|
||||
#include "ck/library/utility/check_err.hpp"
|
||||
#include "ck/library/utility/device_memory.hpp"
|
||||
#include "ck/library/utility/host_tensor.hpp"
|
||||
#include "ck/library/utility/host_tensor_generator.hpp"
|
||||
#include "ck/library/utility/literals.hpp"
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
using Add = ck::tensor_operation::element_wise::Add;
|
||||
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row_Tuple = ck::Tuple<Row>;
|
||||
using F16_Tuple = ck::Tuple<F16>;
|
||||
using BF16_Tuple = ck::Tuple<BF16>;
|
||||
|
||||
struct ProblemSize final
|
||||
{
|
||||
ck::index_t M = 3840;
|
||||
ck::index_t N = 4096;
|
||||
ck::index_t K = 4096;
|
||||
|
||||
ck::index_t StrideA = 4096;
|
||||
ck::index_t StrideB = 4096;
|
||||
ck::index_t StrideD = 4096;
|
||||
ck::index_t StrideE = 4096;
|
||||
};
|
||||
struct ExecutionConfig final
|
||||
{
|
||||
bool do_verification = true;
|
||||
int init_method = 1;
|
||||
bool time_kernel = false;
|
||||
};
|
||||
|
||||
inline bool
|
||||
parse_cmd_args(int argc, char* argv[], ProblemSize& problem_size, ExecutionConfig& config)
|
||||
{
|
||||
if(argc == 1)
|
||||
{
|
||||
// use default case
|
||||
}
|
||||
else if(argc == 4)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
}
|
||||
else if(argc == 6)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
}
|
||||
else if(argc == 13)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
|
||||
problem_size.M = std::stoi(argv[4]);
|
||||
problem_size.N = std::stoi(argv[5]);
|
||||
problem_size.K = std::stoi(argv[6]);
|
||||
|
||||
problem_size.StrideA = std::stoi(argv[7]);
|
||||
problem_size.StrideB = std::stoi(argv[8]);
|
||||
problem_size.StrideD = std::stoi(argv[9]);
|
||||
problem_size.StrideE = std::stoi(argv[10]);
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cerr << "arg1: verification (0=no, 1=yes)" << std::endl
|
||||
<< "arg2: initialization (0=no init, 1=integer value, 2=decimal value)"
|
||||
<< std::endl
|
||||
<< "arg3: time kernel (0=no, 1=yes)" << std::endl
|
||||
<< "arg4 to 10: M (256x), N(128x), K(32x), StrideA, StrideB, StrideD,"
|
||||
"StrideE"
|
||||
<< std::endl;
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
78
example/68_gemm_add/gemm_add_wmma_bf16.cpp
Normal file
78
example/68_gemm_add/gemm_add_wmma_bf16.cpp
Normal file
@@ -0,0 +1,78 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
using ADataType = BF16;
|
||||
using BDataType = BF16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = BF16;
|
||||
using DsDataType = BF16_Tuple;
|
||||
using EDataType = BF16;
|
||||
|
||||
using Row_Tuple = ck::Tuple<Row>;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Row;
|
||||
using DLayout = Row;
|
||||
using DsLayout = Row_Tuple;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = Add;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultipleD_Wmma_CShuffleV3<
|
||||
Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
F32,
|
||||
F32,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add,
|
||||
GemmSpec,
|
||||
128,
|
||||
128,
|
||||
64,
|
||||
64,
|
||||
8,
|
||||
8,
|
||||
16,
|
||||
16,
|
||||
4,
|
||||
2,
|
||||
S<4, 32, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
0,
|
||||
S<4, 32, 1>,
|
||||
S<0, 2, 1>,
|
||||
S<0, 2, 1>,
|
||||
1,
|
||||
1,
|
||||
8,
|
||||
0,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 4>,
|
||||
S<8, 8, 8>,
|
||||
ck::BlockGemmPipelineScheduler::Intrawave,
|
||||
ck::BlockGemmPipelineVersion::v1>;
|
||||
|
||||
// clang-format on
|
||||
|
||||
#include "run_gemm_add_example_wmma.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_example(argc, argv); }
|
||||
76
example/68_gemm_add/gemm_add_wmma_fp16.cpp
Normal file
76
example/68_gemm_add/gemm_add_wmma_fp16.cpp
Normal file
@@ -0,0 +1,76 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
using ADataType = F16;
|
||||
using BDataType = F16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = F16;
|
||||
using DsDataType = F16_Tuple;
|
||||
using EDataType = F16;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Row;
|
||||
using DLayout = Row;
|
||||
using DsLayout = Row_Tuple;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = Add;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultipleD_Wmma_CShuffleV3<
|
||||
Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
F32,
|
||||
F32,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add,
|
||||
GemmSpec,
|
||||
128,
|
||||
128,
|
||||
64,
|
||||
64,
|
||||
8,
|
||||
8,
|
||||
16,
|
||||
16,
|
||||
4,
|
||||
2,
|
||||
S<4, 32, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
0,
|
||||
S<4, 32, 1>,
|
||||
S<0, 2, 1>,
|
||||
S<0, 2, 1>,
|
||||
1,
|
||||
1,
|
||||
8,
|
||||
0,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 4>,
|
||||
S<8, 8, 8>,
|
||||
ck::BlockGemmPipelineScheduler::Intrawave,
|
||||
ck::BlockGemmPipelineVersion::v1>;
|
||||
|
||||
// clang-format on
|
||||
|
||||
#include "run_gemm_add_example_wmma.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_example(argc, argv); }
|
||||
82
example/68_gemm_add/gemm_add_xdl_bf16.cpp
Normal file
82
example/68_gemm_add/gemm_add_xdl_bf16.cpp
Normal file
@@ -0,0 +1,82 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
using ADataType = BF16;
|
||||
using BDataType = BF16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = BF16;
|
||||
using EDataType = BF16;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Col;
|
||||
using DLayout = Row;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = Add;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance =
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD_Xdl_CShuffle<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
CDEElementOp,
|
||||
GemmSpec,
|
||||
1,
|
||||
256,
|
||||
256,
|
||||
128,
|
||||
32,
|
||||
8,
|
||||
8,
|
||||
32,
|
||||
32,
|
||||
4,
|
||||
2,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 8>,
|
||||
8>;
|
||||
|
||||
#include "run_gemm_add_example_xdl.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_example(argc, argv); }
|
||||
82
example/68_gemm_add/gemm_add_xdl_fp16.cpp
Normal file
82
example/68_gemm_add/gemm_add_xdl_fp16.cpp
Normal file
@@ -0,0 +1,82 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
using ADataType = F16;
|
||||
using BDataType = F16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = F16;
|
||||
using EDataType = F16;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Col;
|
||||
using DLayout = Row;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = Add;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance =
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD_Xdl_CShuffle<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
CDEElementOp,
|
||||
GemmSpec,
|
||||
1,
|
||||
256,
|
||||
256,
|
||||
128,
|
||||
32,
|
||||
8,
|
||||
8,
|
||||
32,
|
||||
32,
|
||||
4,
|
||||
2,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 8>,
|
||||
8>;
|
||||
|
||||
#include "run_gemm_add_example_xdl.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_example(argc, argv); }
|
||||
145
example/68_gemm_add/run_gemm_add_example_wmma.inc
Normal file
145
example/68_gemm_add/run_gemm_add_example_wmma.inc
Normal file
@@ -0,0 +1,145 @@
|
||||
#pragma once
|
||||
|
||||
bool run_gemm_add(const ProblemSize& problem_size, const ExecutionConfig& config)
|
||||
{
|
||||
using namespace ck::literals;
|
||||
|
||||
auto& [M, N, K, StrideA, StrideB, StrideD, StrideE] = problem_size;
|
||||
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
|
||||
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {stride, 1_uz});
|
||||
}
|
||||
else
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {1_uz, stride});
|
||||
}
|
||||
};
|
||||
|
||||
Tensor<ADataType> a_m_k(f_host_tensor_descriptor(M, K, StrideA, ALayout{}));
|
||||
Tensor<BDataType> b_k_n(f_host_tensor_descriptor(K, N, StrideB, BLayout{}));
|
||||
Tensor<DDataType> d_m_n(f_host_tensor_descriptor(M, N, StrideD, DLayout{}));
|
||||
Tensor<EDataType> e_m_n_host_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
Tensor<EDataType> e_m_n_device_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
|
||||
std::cout << "a_m_k: " << a_m_k.mDesc << std::endl;
|
||||
std::cout << "b_k_n: " << b_k_n.mDesc << std::endl;
|
||||
std::cout << "d_m_n: " << d_m_n.mDesc << std::endl;
|
||||
std::cout << "e_m_n: " << e_m_n_host_result.mDesc << std::endl;
|
||||
|
||||
switch(config.init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_2<DDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_3<DDataType>{-0.5, 0.5});
|
||||
}
|
||||
|
||||
DeviceMem a_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpaceSize());
|
||||
DeviceMem b_device_buf(sizeof(BDataType) * b_k_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem d_device_buf(sizeof(DDataType) * d_m_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem e_device_buf(sizeof(EDataType) * e_m_n_device_result.mDesc.GetElementSpaceSize());
|
||||
|
||||
a_device_buf.ToDevice(a_m_k.mData.data());
|
||||
b_device_buf.ToDevice(b_k_n.mData.data());
|
||||
d_device_buf.ToDevice(d_m_n.mData.data());
|
||||
e_device_buf.ToDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
auto a_element_op = AElementOp{};
|
||||
auto b_element_op = BElementOp{};
|
||||
auto cde_element_op = CDEElementOp{};
|
||||
|
||||
// do GEMM
|
||||
auto device_op = DeviceOpInstance{};
|
||||
auto invoker = device_op.MakeInvoker();
|
||||
|
||||
auto argument =
|
||||
device_op.MakeArgument(a_device_buf.GetDeviceBuffer(),
|
||||
b_device_buf.GetDeviceBuffer(),
|
||||
std::array<const void*, 1>{d_device_buf.GetDeviceBuffer()},
|
||||
e_device_buf.GetDeviceBuffer(),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<ck::index_t, 1>{StrideD},
|
||||
StrideE,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
|
||||
if(!device_op.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! device_gemm with the specified compilation parameters does "
|
||||
"not support this GEMM problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, config.time_kernel});
|
||||
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype =
|
||||
sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(EDataType) * M * N;
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< device_op.GetTypeString() << std::endl;
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
bool pass = true;
|
||||
if(config.do_verification)
|
||||
{
|
||||
Tensor<CShuffleDataType> c_m_n({M, N});
|
||||
|
||||
using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataType,
|
||||
BDataType,
|
||||
CShuffleDataType,
|
||||
AccDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
PassThrough>;
|
||||
auto ref_gemm = ReferenceGemmInstance{};
|
||||
auto ref_invoker = ref_gemm.MakeInvoker();
|
||||
|
||||
auto ref_argument =
|
||||
ref_gemm.MakeArgument(a_m_k, b_k_n, c_m_n, a_element_op, b_element_op, PassThrough{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
for(int m = 0; m < M; ++m)
|
||||
{
|
||||
for(int n = 0; n < N; ++n)
|
||||
{
|
||||
cde_element_op(e_m_n_host_result(m, n), c_m_n(m, n), d_m_n(m, n));
|
||||
}
|
||||
}
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
pass &= ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
}
|
||||
|
||||
return pass;
|
||||
}
|
||||
|
||||
bool run_gemm_add_example(int argc, char* argv[])
|
||||
{
|
||||
ProblemSize problem_size;
|
||||
ExecutionConfig config;
|
||||
|
||||
return parse_cmd_args(argc, argv, problem_size, config) && run_gemm_add(problem_size, config);
|
||||
}
|
||||
144
example/68_gemm_add/run_gemm_add_example_xdl.inc
Normal file
144
example/68_gemm_add/run_gemm_add_example_xdl.inc
Normal file
@@ -0,0 +1,144 @@
|
||||
#pragma once
|
||||
|
||||
bool run_gemm_add(const ProblemSize& problem_size, const ExecutionConfig& config)
|
||||
{
|
||||
using namespace ck::literals;
|
||||
|
||||
auto& [M, N, K, StrideA, StrideB, StrideD, StrideE] = problem_size;
|
||||
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
|
||||
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {stride, 1_uz});
|
||||
}
|
||||
else
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {1_uz, stride});
|
||||
}
|
||||
};
|
||||
|
||||
Tensor<ADataType> a_m_k(f_host_tensor_descriptor(M, K, StrideA, ALayout{}));
|
||||
Tensor<BDataType> b_k_n(f_host_tensor_descriptor(K, N, StrideB, BLayout{}));
|
||||
Tensor<DDataType> d_m_n(f_host_tensor_descriptor(M, N, StrideD, DLayout{}));
|
||||
Tensor<EDataType> e_m_n_host_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
Tensor<EDataType> e_m_n_device_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
|
||||
std::cout << "a_m_k: " << a_m_k.mDesc << std::endl;
|
||||
std::cout << "b_k_n: " << b_k_n.mDesc << std::endl;
|
||||
std::cout << "d_m_n: " << d_m_n.mDesc << std::endl;
|
||||
std::cout << "e_m_n: " << e_m_n_host_result.mDesc << std::endl;
|
||||
|
||||
switch(config.init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_2<DDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_3<DDataType>{-0.5, 0.5});
|
||||
}
|
||||
|
||||
DeviceMem a_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpaceSize());
|
||||
DeviceMem b_device_buf(sizeof(BDataType) * b_k_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem d_device_buf(sizeof(DDataType) * d_m_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem e_device_buf(sizeof(EDataType) * e_m_n_device_result.mDesc.GetElementSpaceSize());
|
||||
|
||||
a_device_buf.ToDevice(a_m_k.mData.data());
|
||||
b_device_buf.ToDevice(b_k_n.mData.data());
|
||||
d_device_buf.ToDevice(d_m_n.mData.data());
|
||||
e_device_buf.ToDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
auto a_element_op = AElementOp{};
|
||||
auto b_element_op = BElementOp{};
|
||||
auto cde_element_op = CDEElementOp{};
|
||||
|
||||
// do GEMM
|
||||
auto device_op = DeviceOpInstance{};
|
||||
auto invoker = device_op.MakeInvoker();
|
||||
|
||||
auto argument =
|
||||
device_op.MakeArgument(a_device_buf.GetDeviceBuffer(),
|
||||
b_device_buf.GetDeviceBuffer(),
|
||||
std::array<const void*, 1>{d_device_buf.GetDeviceBuffer()},
|
||||
e_device_buf.GetDeviceBuffer(),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<ck::index_t, 1>{StrideD},
|
||||
StrideE,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
|
||||
if(!device_op.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! device_gemm with the specified compilation parameters does "
|
||||
"not support this GEMM problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, config.time_kernel});
|
||||
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype =
|
||||
sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(EDataType) * M * N;
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< device_op.GetTypeString() << std::endl;
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
bool pass = true;
|
||||
if(config.do_verification)
|
||||
{
|
||||
Tensor<CShuffleDataType> c_m_n({M, N});
|
||||
|
||||
using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataType,
|
||||
BDataType,
|
||||
CShuffleDataType,
|
||||
AccDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
PassThrough>;
|
||||
auto ref_gemm = ReferenceGemmInstance{};
|
||||
auto ref_invoker = ref_gemm.MakeInvoker();
|
||||
|
||||
auto ref_argument =
|
||||
ref_gemm.MakeArgument(a_m_k, b_k_n, c_m_n, a_element_op, b_element_op, PassThrough{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
for(int m = 0; m < M; ++m)
|
||||
{
|
||||
for(int n = 0; n < N; ++n)
|
||||
{
|
||||
cde_element_op(e_m_n_host_result(m, n), c_m_n(m, n), d_m_n(m, n));
|
||||
}
|
||||
}
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
pass &= ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
}
|
||||
|
||||
return pass;
|
||||
}
|
||||
|
||||
bool run_gemm_add_example(int argc, char* argv[])
|
||||
{
|
||||
ProblemSize problem_size;
|
||||
ExecutionConfig config;
|
||||
|
||||
return parse_cmd_args(argc, argv, problem_size, config) && run_gemm_add(problem_size, config);
|
||||
}
|
||||
15
example/69_gemm_add_relu/CMakeLists.txt
Normal file
15
example/69_gemm_add_relu/CMakeLists.txt
Normal file
@@ -0,0 +1,15 @@
|
||||
add_custom_target(example_gemm_add_relu_xdl)
|
||||
|
||||
add_example_executable(example_gemm_add_relu_xdl_fp16 gemm_add_relu_xdl_fp16.cpp)
|
||||
add_example_dependencies(example_gemm_add_relu_xdl example_gemm_add_relu_xdl_fp16)
|
||||
|
||||
add_example_executable(example_gemm_add_relu_xdl_bf16 gemm_add_relu_xdl_bf16.cpp)
|
||||
add_example_dependencies(example_gemm_add_relu_xdl example_gemm_add_relu_xdl_bf16)
|
||||
|
||||
add_custom_target(example_gemm_add_relu_wmma)
|
||||
|
||||
add_example_executable(example_gemm_add_relu_wmma_bf16 gemm_add_relu_wmma_bf16.cpp)
|
||||
add_example_dependencies(example_gemm_add_relu_wmma example_gemm_add_relu_wmma_bf16)
|
||||
|
||||
add_example_executable(example_gemm_add_relu_wmma_fp16 gemm_add_relu_wmma_fp16.cpp)
|
||||
add_example_dependencies(example_gemm_add_relu_wmma example_gemm_add_relu_wmma_fp16)
|
||||
114
example/69_gemm_add_relu/common.hpp
Normal file
114
example/69_gemm_add_relu/common.hpp
Normal file
@@ -0,0 +1,114 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <algorithm>
|
||||
#include <cstddef>
|
||||
#include <iostream>
|
||||
#include <stdexcept>
|
||||
#include <string>
|
||||
|
||||
#include "ck/ck.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
#include "ck/utility/data_type.hpp"
|
||||
|
||||
#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
|
||||
#include "ck/library/utility/check_err.hpp"
|
||||
#include "ck/library/utility/device_memory.hpp"
|
||||
#include "ck/library/utility/host_tensor.hpp"
|
||||
#include "ck/library/utility/host_tensor_generator.hpp"
|
||||
#include "ck/library/utility/literals.hpp"
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
using AddRelu = ck::tensor_operation::element_wise::AddRelu;
|
||||
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row_Tuple = ck::Tuple<Row>;
|
||||
using F16_Tuple = ck::Tuple<F16>;
|
||||
using BF16_Tuple = ck::Tuple<BF16>;
|
||||
|
||||
struct ProblemSize final
|
||||
{
|
||||
ck::index_t M = 3840;
|
||||
ck::index_t N = 4096;
|
||||
ck::index_t K = 4096;
|
||||
|
||||
ck::index_t StrideA = 4096;
|
||||
ck::index_t StrideB = 4096;
|
||||
ck::index_t StrideD = 4096;
|
||||
ck::index_t StrideE = 4096;
|
||||
};
|
||||
struct ExecutionConfig final
|
||||
{
|
||||
bool do_verification = true;
|
||||
int init_method = 1;
|
||||
bool time_kernel = false;
|
||||
};
|
||||
|
||||
inline bool
|
||||
parse_cmd_args(int argc, char* argv[], ProblemSize& problem_size, ExecutionConfig& config)
|
||||
{
|
||||
if(argc == 1)
|
||||
{
|
||||
// use default case
|
||||
}
|
||||
else if(argc == 4)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
}
|
||||
else if(argc == 6)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
}
|
||||
else if(argc == 13)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
|
||||
problem_size.M = std::stoi(argv[4]);
|
||||
problem_size.N = std::stoi(argv[5]);
|
||||
problem_size.K = std::stoi(argv[6]);
|
||||
|
||||
problem_size.StrideA = std::stoi(argv[7]);
|
||||
problem_size.StrideB = std::stoi(argv[8]);
|
||||
problem_size.StrideD = std::stoi(argv[9]);
|
||||
problem_size.StrideE = std::stoi(argv[10]);
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cerr << "arg1: verification (0=no, 1=yes)" << std::endl
|
||||
<< "arg2: initialization (0=no init, 1=integer value, 2=decimal value)"
|
||||
<< std::endl
|
||||
<< "arg3: time kernel (0=no, 1=yes)" << std::endl
|
||||
<< "arg4 to 10: M (256x), N(128x), K(32x), StrideA, StrideB, StrideD,"
|
||||
"StrideE"
|
||||
<< std::endl;
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
78
example/69_gemm_add_relu/gemm_add_relu_wmma_bf16.cpp
Normal file
78
example/69_gemm_add_relu/gemm_add_relu_wmma_bf16.cpp
Normal file
@@ -0,0 +1,78 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
using ADataType = BF16;
|
||||
using BDataType = BF16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = BF16;
|
||||
using DsDataType = BF16_Tuple;
|
||||
using EDataType = BF16;
|
||||
|
||||
using Row_Tuple = ck::Tuple<Row>;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Row;
|
||||
using DLayout = Row;
|
||||
using DsLayout = Row_Tuple;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = AddRelu;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultipleD_Wmma_CShuffleV3<
|
||||
Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
F32,
|
||||
F32,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu,
|
||||
GemmSpec,
|
||||
128,
|
||||
128,
|
||||
64,
|
||||
64,
|
||||
8,
|
||||
8,
|
||||
16,
|
||||
16,
|
||||
4,
|
||||
2,
|
||||
S<4, 32, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
0,
|
||||
S<4, 32, 1>,
|
||||
S<0, 2, 1>,
|
||||
S<0, 2, 1>,
|
||||
1,
|
||||
1,
|
||||
8,
|
||||
0,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 4>,
|
||||
S<8, 8, 8>,
|
||||
ck::BlockGemmPipelineScheduler::Intrawave,
|
||||
ck::BlockGemmPipelineVersion::v1>;
|
||||
|
||||
// clang-format on
|
||||
|
||||
#include "run_gemm_add_relu_example_wmma.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_relu_example(argc, argv); }
|
||||
76
example/69_gemm_add_relu/gemm_add_relu_wmma_fp16.cpp
Normal file
76
example/69_gemm_add_relu/gemm_add_relu_wmma_fp16.cpp
Normal file
@@ -0,0 +1,76 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
using ADataType = F16;
|
||||
using BDataType = F16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = F16;
|
||||
using DsDataType = F16_Tuple;
|
||||
using EDataType = F16;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Row;
|
||||
using DLayout = Row;
|
||||
using DsLayout = Row_Tuple;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = AddRelu;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultipleD_Wmma_CShuffleV3<
|
||||
Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
F32,
|
||||
F32,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu,
|
||||
GemmSpec,
|
||||
128,
|
||||
128,
|
||||
64,
|
||||
64,
|
||||
8,
|
||||
8,
|
||||
16,
|
||||
16,
|
||||
4,
|
||||
2,
|
||||
S<4, 32, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
0,
|
||||
S<4, 32, 1>,
|
||||
S<0, 2, 1>,
|
||||
S<0, 2, 1>,
|
||||
1,
|
||||
1,
|
||||
8,
|
||||
0,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 4>,
|
||||
S<8, 8, 8>,
|
||||
ck::BlockGemmPipelineScheduler::Intrawave,
|
||||
ck::BlockGemmPipelineVersion::v1>;
|
||||
|
||||
// clang-format on
|
||||
|
||||
#include "run_gemm_add_relu_example_wmma.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_relu_example(argc, argv); }
|
||||
82
example/69_gemm_add_relu/gemm_add_relu_xdl_bf16.cpp
Normal file
82
example/69_gemm_add_relu/gemm_add_relu_xdl_bf16.cpp
Normal file
@@ -0,0 +1,82 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
using ADataType = BF16;
|
||||
using BDataType = BF16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = BF16;
|
||||
using EDataType = BF16;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Col;
|
||||
using DLayout = Row;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = AddRelu;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance =
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD_Xdl_CShuffle<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
CDEElementOp,
|
||||
GemmSpec,
|
||||
1,
|
||||
256,
|
||||
256,
|
||||
128,
|
||||
32,
|
||||
8,
|
||||
8,
|
||||
32,
|
||||
32,
|
||||
4,
|
||||
2,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 8>,
|
||||
8>;
|
||||
|
||||
#include "run_gemm_add_relu_example_xdl.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_relu_example(argc, argv); }
|
||||
82
example/69_gemm_add_relu/gemm_add_relu_xdl_fp16.cpp
Normal file
82
example/69_gemm_add_relu/gemm_add_relu_xdl_fp16.cpp
Normal file
@@ -0,0 +1,82 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "common.hpp"
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
using ADataType = F16;
|
||||
using BDataType = F16;
|
||||
using AccDataType = F32;
|
||||
using CShuffleDataType = F32;
|
||||
using DDataType = F16;
|
||||
using EDataType = F16;
|
||||
|
||||
using ALayout = Row;
|
||||
using BLayout = Col;
|
||||
using DLayout = Row;
|
||||
using ELayout = Row;
|
||||
|
||||
using AElementOp = PassThrough;
|
||||
using BElementOp = PassThrough;
|
||||
using CDEElementOp = AddRelu;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceOpInstance =
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD_Xdl_CShuffle<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
CDEElementOp,
|
||||
GemmSpec,
|
||||
1,
|
||||
256,
|
||||
256,
|
||||
128,
|
||||
32,
|
||||
8,
|
||||
8,
|
||||
32,
|
||||
32,
|
||||
4,
|
||||
2,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
S<4, 64, 1>,
|
||||
S<1, 0, 2>,
|
||||
S<1, 0, 2>,
|
||||
2,
|
||||
8,
|
||||
8,
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
S<1, 32, 1, 8>,
|
||||
8>;
|
||||
|
||||
#include "run_gemm_add_relu_example_xdl.inc"
|
||||
|
||||
int main(int argc, char* argv[]) { return !run_gemm_add_relu_example(argc, argv); }
|
||||
146
example/69_gemm_add_relu/run_gemm_add_relu_example_wmma.inc
Normal file
146
example/69_gemm_add_relu/run_gemm_add_relu_example_wmma.inc
Normal file
@@ -0,0 +1,146 @@
|
||||
#pragma once
|
||||
|
||||
bool run_gemm_add_relu(const ProblemSize& problem_size, const ExecutionConfig& config)
|
||||
{
|
||||
using namespace ck::literals;
|
||||
|
||||
auto& [M, N, K, StrideA, StrideB, StrideD, StrideE] = problem_size;
|
||||
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
|
||||
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {stride, 1_uz});
|
||||
}
|
||||
else
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {1_uz, stride});
|
||||
}
|
||||
};
|
||||
|
||||
Tensor<ADataType> a_m_k(f_host_tensor_descriptor(M, K, StrideA, ALayout{}));
|
||||
Tensor<BDataType> b_k_n(f_host_tensor_descriptor(K, N, StrideB, BLayout{}));
|
||||
Tensor<DDataType> d_m_n(f_host_tensor_descriptor(M, N, StrideD, DLayout{}));
|
||||
Tensor<EDataType> e_m_n_host_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
Tensor<EDataType> e_m_n_device_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
|
||||
std::cout << "a_m_k: " << a_m_k.mDesc << std::endl;
|
||||
std::cout << "b_k_n: " << b_k_n.mDesc << std::endl;
|
||||
std::cout << "d_m_n: " << d_m_n.mDesc << std::endl;
|
||||
std::cout << "e_m_n: " << e_m_n_host_result.mDesc << std::endl;
|
||||
|
||||
switch(config.init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_2<DDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_3<DDataType>{-0.5, 0.5});
|
||||
}
|
||||
|
||||
DeviceMem a_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpaceSize());
|
||||
DeviceMem b_device_buf(sizeof(BDataType) * b_k_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem d_device_buf(sizeof(DDataType) * d_m_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem e_device_buf(sizeof(EDataType) * e_m_n_device_result.mDesc.GetElementSpaceSize());
|
||||
|
||||
a_device_buf.ToDevice(a_m_k.mData.data());
|
||||
b_device_buf.ToDevice(b_k_n.mData.data());
|
||||
d_device_buf.ToDevice(d_m_n.mData.data());
|
||||
e_device_buf.ToDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
auto a_element_op = AElementOp{};
|
||||
auto b_element_op = BElementOp{};
|
||||
auto cde_element_op = CDEElementOp{};
|
||||
|
||||
// do GEMM
|
||||
auto device_op = DeviceOpInstance{};
|
||||
auto invoker = device_op.MakeInvoker();
|
||||
|
||||
auto argument =
|
||||
device_op.MakeArgument(a_device_buf.GetDeviceBuffer(),
|
||||
b_device_buf.GetDeviceBuffer(),
|
||||
std::array<const void*, 1>{d_device_buf.GetDeviceBuffer()},
|
||||
e_device_buf.GetDeviceBuffer(),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<ck::index_t, 1>{StrideD},
|
||||
StrideE,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
|
||||
if(!device_op.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! device_gemm with the specified compilation parameters does "
|
||||
"not support this GEMM problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, config.time_kernel});
|
||||
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype =
|
||||
sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(EDataType) * M * N;
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< device_op.GetTypeString() << std::endl;
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
bool pass = true;
|
||||
if(config.do_verification)
|
||||
{
|
||||
Tensor<CShuffleDataType> c_m_n({M, N});
|
||||
|
||||
using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataType,
|
||||
BDataType,
|
||||
CShuffleDataType,
|
||||
AccDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
PassThrough>;
|
||||
auto ref_gemm = ReferenceGemmInstance{};
|
||||
auto ref_invoker = ref_gemm.MakeInvoker();
|
||||
|
||||
auto ref_argument =
|
||||
ref_gemm.MakeArgument(a_m_k, b_k_n, c_m_n, a_element_op, b_element_op, PassThrough{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
for(int m = 0; m < M; ++m)
|
||||
{
|
||||
for(int n = 0; n < N; ++n)
|
||||
{
|
||||
cde_element_op(e_m_n_host_result(m, n), c_m_n(m, n), d_m_n(m, n));
|
||||
}
|
||||
}
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
pass &= ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
}
|
||||
|
||||
return pass;
|
||||
}
|
||||
|
||||
bool run_gemm_add_relu_example(int argc, char* argv[])
|
||||
{
|
||||
ProblemSize problem_size;
|
||||
ExecutionConfig config;
|
||||
|
||||
return parse_cmd_args(argc, argv, problem_size, config) &&
|
||||
run_gemm_add_relu(problem_size, config);
|
||||
}
|
||||
145
example/69_gemm_add_relu/run_gemm_add_relu_example_xdl.inc
Normal file
145
example/69_gemm_add_relu/run_gemm_add_relu_example_xdl.inc
Normal file
@@ -0,0 +1,145 @@
|
||||
#pragma once
|
||||
|
||||
bool run_gemm_add_relu(const ProblemSize& problem_size, const ExecutionConfig& config)
|
||||
{
|
||||
using namespace ck::literals;
|
||||
|
||||
auto& [M, N, K, StrideA, StrideB, StrideD, StrideE] = problem_size;
|
||||
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
|
||||
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {stride, 1_uz});
|
||||
}
|
||||
else
|
||||
{
|
||||
return HostTensorDescriptor({row, col}, {1_uz, stride});
|
||||
}
|
||||
};
|
||||
|
||||
Tensor<ADataType> a_m_k(f_host_tensor_descriptor(M, K, StrideA, ALayout{}));
|
||||
Tensor<BDataType> b_k_n(f_host_tensor_descriptor(K, N, StrideB, BLayout{}));
|
||||
Tensor<DDataType> d_m_n(f_host_tensor_descriptor(M, N, StrideD, DLayout{}));
|
||||
Tensor<EDataType> e_m_n_host_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
Tensor<EDataType> e_m_n_device_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
|
||||
|
||||
std::cout << "a_m_k: " << a_m_k.mDesc << std::endl;
|
||||
std::cout << "b_k_n: " << b_k_n.mDesc << std::endl;
|
||||
std::cout << "d_m_n: " << d_m_n.mDesc << std::endl;
|
||||
std::cout << "e_m_n: " << e_m_n_host_result.mDesc << std::endl;
|
||||
|
||||
switch(config.init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_2<DDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
|
||||
b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
|
||||
d_m_n.GenerateTensorValue(GeneratorTensor_3<DDataType>{-0.5, 0.5});
|
||||
}
|
||||
|
||||
DeviceMem a_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpaceSize());
|
||||
DeviceMem b_device_buf(sizeof(BDataType) * b_k_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem d_device_buf(sizeof(DDataType) * d_m_n.mDesc.GetElementSpaceSize());
|
||||
DeviceMem e_device_buf(sizeof(EDataType) * e_m_n_device_result.mDesc.GetElementSpaceSize());
|
||||
|
||||
a_device_buf.ToDevice(a_m_k.mData.data());
|
||||
b_device_buf.ToDevice(b_k_n.mData.data());
|
||||
d_device_buf.ToDevice(d_m_n.mData.data());
|
||||
e_device_buf.ToDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
auto a_element_op = AElementOp{};
|
||||
auto b_element_op = BElementOp{};
|
||||
auto cde_element_op = CDEElementOp{};
|
||||
|
||||
// do GEMM
|
||||
auto device_op = DeviceOpInstance{};
|
||||
auto invoker = device_op.MakeInvoker();
|
||||
|
||||
auto argument =
|
||||
device_op.MakeArgument(a_device_buf.GetDeviceBuffer(),
|
||||
b_device_buf.GetDeviceBuffer(),
|
||||
std::array<const void*, 1>{d_device_buf.GetDeviceBuffer()},
|
||||
e_device_buf.GetDeviceBuffer(),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<ck::index_t, 1>{StrideD},
|
||||
StrideE,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
|
||||
if(!device_op.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! device_gemm with the specified compilation parameters does "
|
||||
"not support this GEMM problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, StreamConfig{nullptr, config.time_kernel});
|
||||
|
||||
std::size_t flop = std::size_t(2) * M * N * K;
|
||||
std::size_t num_btype =
|
||||
sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(EDataType) * M * N;
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< device_op.GetTypeString() << std::endl;
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
bool pass = true;
|
||||
if(config.do_verification)
|
||||
{
|
||||
Tensor<CShuffleDataType> c_m_n({M, N});
|
||||
|
||||
using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataType,
|
||||
BDataType,
|
||||
CShuffleDataType,
|
||||
AccDataType,
|
||||
AElementOp,
|
||||
BElementOp,
|
||||
PassThrough>;
|
||||
auto ref_gemm = ReferenceGemmInstance{};
|
||||
auto ref_invoker = ref_gemm.MakeInvoker();
|
||||
|
||||
auto ref_argument =
|
||||
ref_gemm.MakeArgument(a_m_k, b_k_n, c_m_n, a_element_op, b_element_op, PassThrough{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
for(int m = 0; m < M; ++m)
|
||||
{
|
||||
for(int n = 0; n < N; ++n)
|
||||
{
|
||||
cde_element_op(e_m_n_host_result(m, n), c_m_n(m, n), d_m_n(m, n));
|
||||
}
|
||||
}
|
||||
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
pass &= ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
}
|
||||
|
||||
return pass;
|
||||
}
|
||||
|
||||
bool run_gemm_add_relu_example(int argc, char* argv[])
|
||||
{
|
||||
ProblemSize problem_size;
|
||||
ExecutionConfig config;
|
||||
|
||||
return parse_cmd_args(argc, argv, problem_size, config) &&
|
||||
run_gemm_add_relu(problem_size, config);
|
||||
}
|
||||
2
example/ck_tile/01_fmha/mask.hpp
Executable file → Normal file
2
example/ck_tile/01_fmha/mask.hpp
Executable file → Normal file
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
|
||||
@@ -149,50 +149,105 @@ struct DeviceGemmMultipleDSplitKBPreShuffle : public BaseOperator
|
||||
#endif
|
||||
};
|
||||
|
||||
/// @brief Wrapper for backward compatibility that allows to use instances of
|
||||
/// DeviceGemmMultipleDSplitK in contexts where DeviceGemmMultipleD is expected.
|
||||
///
|
||||
/// @note The main area where it can be used is DeviceOperationInstanceFactory::GetInstances().
|
||||
/// The only difference between API of DeviceGemmMultipleD and DeviceGemmMultipleDSplitK is
|
||||
/// that DeviceGemmMultipleDSplitK::MakeArgumentPointer requires an additional parameter
|
||||
/// KBatch which is explicitly passed as 1 by this wrapper.
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename DsLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename AScaleDataType,
|
||||
typename BDataType,
|
||||
typename BScaleDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
index_t ScaleBlockSize,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation>
|
||||
struct DeviceMoEGemmMXBPreShuffle : public BaseOperator
|
||||
struct DeviceGemmMultipleDSplitKWrapper : public DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation>;
|
||||
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
#ifndef CK_CODE_GEN_RTC
|
||||
virtual std::unique_ptr<BaseArgument>
|
||||
#ifndef __HIPCC_RTC__
|
||||
|
||||
explicit DeviceGemmMultipleDSplitKWrapper(std::unique_ptr<DeviceOp> p_op)
|
||||
: p_op_(std::move(p_op))
|
||||
{
|
||||
}
|
||||
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return p_op_->IsSupportedArgument(p_arg);
|
||||
}
|
||||
std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(const void* p_a,
|
||||
const void* p_a_scale,
|
||||
const void* p_b,
|
||||
const void* p_b_scale,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_e,
|
||||
ck::index_t M,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t StrideA,
|
||||
ck::index_t StrideAScale,
|
||||
ck::index_t StrideB,
|
||||
ck::index_t StrideBScale,
|
||||
std::array<ck::index_t, NumDTensor> StrideDs,
|
||||
ck::index_t StrideE,
|
||||
ck::index_t KBatch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op) = 0;
|
||||
CDEElementwiseOperation cde_element_op) override
|
||||
{
|
||||
return p_op_->MakeArgumentPointer(p_a,
|
||||
p_b,
|
||||
p_ds,
|
||||
p_e,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideDs,
|
||||
StrideE,
|
||||
1, // KBatch
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
}
|
||||
|
||||
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
|
||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
|
||||
return p_op_->MakeInvokerPointer();
|
||||
}
|
||||
|
||||
virtual int GetPreShuffleParameters() = 0;
|
||||
#endif
|
||||
std::string GetTypeString() const override { return p_op_->GetTypeString(); }
|
||||
|
||||
private:
|
||||
std::unique_ptr<DeviceOp> p_op_;
|
||||
|
||||
#endif // __HIPCC_RTC__
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
|
||||
@@ -40,7 +40,7 @@ __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
|
||||
#if(defined(__gfx11__) || defined(__gfx12__))
|
||||
#if defined(__gfx11__)
|
||||
// gfx11 does not support *_atomic_pk_add_f16/bf16 instructions
|
||||
using c_data_type = remove_cvref_t<remove_pointer_t<decltype(karg.p_c_grid)>>;
|
||||
using c_data_type = remove_cvref_t<remove_pointer_t<decltype(karg.p_e_grid)>>;
|
||||
if constexpr(!(CGlobalMemoryDataOperation == InMemoryDataOperationEnum::AtomicAdd &&
|
||||
(std::is_same_v<c_data_type, ck::half_t> ||
|
||||
std::is_same_v<c_data_type, ck::bhalf_t>)))
|
||||
@@ -62,14 +62,18 @@ __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
|
||||
|
||||
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
|
||||
|
||||
auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg);
|
||||
auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg, blockIdx.z);
|
||||
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop, CGlobalMemoryDataOperation, TailNum>(
|
||||
karg.p_a_grid + splitk_batch_offset.a_k_split_offset + a_batch_offset,
|
||||
karg.p_b_grid + splitk_batch_offset.b_k_split_offset + b_batch_offset,
|
||||
karg.p_c_grid + splitk_batch_offset.c_reduce_offset + c_batch_offset,
|
||||
karg.p_ds_grid,
|
||||
karg.p_e_grid + splitk_batch_offset.c_reduce_offset + c_batch_offset,
|
||||
p_shared,
|
||||
karg);
|
||||
karg,
|
||||
karg.a_element_op,
|
||||
karg.b_element_op,
|
||||
karg.cde_element_op);
|
||||
#if defined(__gfx11__)
|
||||
}
|
||||
#endif
|
||||
@@ -272,11 +276,13 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
using GridwiseGemm = GridwiseGemm_wmma_cshuffle_v3<
|
||||
ALayout,
|
||||
BLayout,
|
||||
Tuple<>, // DsLayout
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
Tuple<>, // DsDataType
|
||||
CDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
@@ -311,7 +317,7 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
Sequence<CShuffleBlockTransferScalarPerVector_NPerBlock>,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -336,17 +342,25 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
index_t BatchStrideC_,
|
||||
index_t Batch_,
|
||||
index_t k_batch_,
|
||||
AElementwiseOperation a_element_op_,
|
||||
BElementwiseOperation b_element_op_,
|
||||
CElementwiseOperation cde_element_op_,
|
||||
bool is_reduce_ = false)
|
||||
: GridwiseGemm::Argument(p_a_grid_,
|
||||
p_b_grid_,
|
||||
std::array<const void*, 0>{}, // p_ds_grid_
|
||||
p_c_grid_,
|
||||
M_,
|
||||
N_,
|
||||
K_,
|
||||
StrideA_,
|
||||
StrideB_,
|
||||
std::array<index_t, 0>{}, // StrideDs_
|
||||
StrideC_,
|
||||
k_batch_,
|
||||
a_element_op_,
|
||||
b_element_op_,
|
||||
cde_element_op_,
|
||||
is_reduce_),
|
||||
Batch(Batch_),
|
||||
compute_ptr_offset_of_batch{BatchStrideA_, BatchStrideB_, BatchStrideC_}
|
||||
@@ -443,7 +457,7 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
// Note: This seems incorrect for non-contiguous memory layouts for C
|
||||
// (padding, gaps).
|
||||
HIP_CHECK_ERROR(
|
||||
hipMemsetAsync(arg_.p_c_grid,
|
||||
hipMemsetAsync(arg_.p_e_grid,
|
||||
0,
|
||||
arg_.Batch * arg_.M * arg_.N * sizeof(CDataType),
|
||||
stream_config.stream_id_));
|
||||
@@ -469,7 +483,7 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
// Note: This seems incorrect for non-contiguous memory layouts for C
|
||||
// (padding, gaps).
|
||||
HIP_CHECK_ERROR(
|
||||
hipMemsetAsync(arg.p_c_grid,
|
||||
hipMemsetAsync(arg.p_e_grid,
|
||||
0,
|
||||
arg.Batch * arg.M * arg.N * sizeof(CDataType),
|
||||
stream_config.stream_id_));
|
||||
@@ -658,7 +672,10 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
BatchStrideB,
|
||||
BatchStrideC,
|
||||
Batch,
|
||||
1 /* KBatch */};
|
||||
1, /* KBatch */
|
||||
AElementwiseOperation{},
|
||||
BElementwiseOperation{},
|
||||
CElementwiseOperation{}};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
@@ -694,7 +711,10 @@ struct DeviceBatchedGemm_Wmma_CShuffleV3 : public DeviceBatchedGemm<ALayout,
|
||||
BatchStrideB,
|
||||
BatchStrideC,
|
||||
Batch,
|
||||
1); // KBatch
|
||||
1,
|
||||
AElementwiseOperation{},
|
||||
BElementwiseOperation{},
|
||||
CElementwiseOperation{}); // KBatch
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
|
||||
@@ -0,0 +1,410 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
|
||||
#include "ck/utility/common_header.hpp"
|
||||
#include "ck/tensor_description/tensor_descriptor.hpp"
|
||||
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/host_utility/device_prop.hpp"
|
||||
#include "ck/host_utility/kernel_launch.hpp"
|
||||
#include "ck/host_utility/flush_cache.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_wmma_cshuffle_v3_common.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
/// @brief \"Universal\" GEMM operation with SplitK support and multiple D tensors.
|
||||
///
|
||||
/// @par Overview
|
||||
/// This GEMM operation implements the following mathematical equation:
|
||||
/// E{M,N} = CDE_op(A_op(A{M,K}) * B_op(B{K,N}), Ds{M,N}...)
|
||||
/// Where A, B, Ds are input tensors and E is the output tensor. The A/B are elementwise
|
||||
// operations that could be applied on each tensor respectively. The CDE_op is an
|
||||
// elementwise operation applied to the C and all D tensors.
|
||||
/// The \"universal\" gemm comes with multiple pipelines optimized for different usage
|
||||
/// scenarios. That's why it's called \"universal\". It's universal through it's design
|
||||
/// and versatilty.
|
||||
///
|
||||
/// @note This Kernel implementation supports SplitK algorithm. It can be configured
|
||||
/// to split the dot product accumulated over the K dimension into multiple working groups.
|
||||
/// The partial products of different workgroups are then reduced using the AtomicAdd
|
||||
/// operation.
|
||||
///
|
||||
/// @tparam ALayout A tensor data layout.
|
||||
/// @tparam BLayout B tensor data layout.
|
||||
/// @tparam DsLayout D tensors data layouts.
|
||||
/// @tparam ELayout E tensor data layout.
|
||||
/// @tparam ADataType A tensor data type.
|
||||
/// @tparam BDataType B tensor data type.
|
||||
/// @tparam DsDataType D tensors data types.
|
||||
/// @tparam EDataType E tensor data type.
|
||||
/// @tparam AccDataType The accumulation data type related to the hardware
|
||||
/// matrix-multiplication instruction.
|
||||
/// @tparam CShuffleDataType The data type used to store matrix-multiplication results into
|
||||
/// LDS memory during \"CShuffle\" data layout optimization.
|
||||
/// @tparam AElementwiseOperation Elementwise operation applied to the A input tensor elements.
|
||||
/// @tparam BElementwiseOperation Elementwise operation applied to the B input tensor elements.
|
||||
/// @tparam CDEElementwiseOperation Elementwise operation applied to the C output tensor (after
|
||||
/// GEMM) and D input tensors.
|
||||
/// @tparam GemmSpec Determines used "padding" version.
|
||||
/// @tparam BlockSize The number of threads within workgroup.
|
||||
/// @tparam MPerBlock The input/output data tile size in the M dimension.
|
||||
/// @tparam NPerBlock The input/output data tile size in the N dimension.
|
||||
/// @tparam KPerBlock The input data tile size in the K dimension.
|
||||
/// @tparam AK1 The vector load size from global memory for A tensor.
|
||||
/// @tparam BK1 The vector load size from global memory for B tensor.
|
||||
/// @tparam MPerWmma M size of Wave Matrix Multiply Accumulate (WMMA) instruction.
|
||||
/// @tparam NPerWmma N size of Wave Matrix Multiply Accumulate (WMMA) instruction.
|
||||
/// @tparam MRepeat The number of iterations in the M dimension over output tile per wavefront.
|
||||
/// @tparam NRepeat The number of iterations in the N dimension over output tile per wavefront.
|
||||
/// @tparam ABlockTransferThreadClusterLengths_AK0_M_AK1 Spatial thread distribution over the input
|
||||
/// data. Can be interpreted as the answer
|
||||
/// to the question, "How many threads can be
|
||||
/// arranged on each input data axis?"
|
||||
/// @tparam ABlockTransferThreadClusterArrangeOrder The order of thread spatial distribution over
|
||||
/// the input tensor dimension. Can be interpreted
|
||||
/// as the answer to the question: "In which
|
||||
/// order to spread threads through tensor axes?".
|
||||
/// @tparam ABlockTransferSrcAccessOrder The order of accessing input tensor axes. Can be
|
||||
/// interpreted as the answer to the question "Which dimension
|
||||
/// to read first? And which next?" etc.
|
||||
/// @tparam ABlockTransferSrcVectorDim The index of axis on which we could do vectorized memory
|
||||
/// access - the one with contiguous memory.
|
||||
/// @tparam ABlockTransferSrcScalarPerVector The size of vector access instruction - the number of
|
||||
/// elements accessed per thread per instruction.
|
||||
/// @tparam ABlockTransferDstScalarPerVector_AK1 The size of vectorized store into LDS memory.
|
||||
/// @tparam ABlockLdsExtraM Whether to use padding for LDS or not. With
|
||||
/// universal GEMM there's no need for padding.
|
||||
/// @tparam BBlockTransferThreadClusterLengths_BK0_N_BK1 Spatial thread distribution over the input
|
||||
/// data. Can be interpreted as the answer
|
||||
/// to the question: "How many threads to
|
||||
/// arrange on each input data axis?"
|
||||
/// @tparam BBlockTransferThreadClusterArrangeOrder The order of thread spatial distribution over
|
||||
/// the input tensor dimension. Can be interpreted
|
||||
/// as the answer to the question: "In which
|
||||
/// order to spread threads through tensor axes?".
|
||||
/// @tparam BBlockTransferSrcAccessOrder he order of accessing input tensor axes. Can be
|
||||
/// interpreted as the answer to the question "Which dimension
|
||||
/// to read first? And which next?" etc.
|
||||
/// @tparam BBlockTransferSrcVectorDim The index of axis on which we could do vectorized memory
|
||||
/// access - the one with contiguous memory.
|
||||
/// @tparam BBlockTransferSrcScalarPerVector The size of vector access instruction - the number of
|
||||
/// elements accessed per thread per instruction.
|
||||
/// @tparam BBlockTransferDstScalarPerVector_BK1 The size of vectorized store into LDS memory.
|
||||
/// @tparam BBlockLdsExtraN Whether to use padding for LDS or not. With
|
||||
/// universal GEMM there's no need for padding.
|
||||
/// @tparam CShuffleMRepeatPerShuffle The number of matrix-multiplication instructions
|
||||
/// results to process per wave per iteration of CShuffle
|
||||
/// in M dimension.
|
||||
/// @tparam CShuffleNRepeatPerShuffle The number of matrix-multiplication instructions
|
||||
/// results to process per wave per iteration of CShuffle
|
||||
/// in N dimension.
|
||||
/// @tparam CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock The spatial
|
||||
/// thread distribution used for storing data into output
|
||||
/// tensor across output data layout dimensions.
|
||||
/// @tparam CDEShuffleBlockTransferScalarPerVectors The size of vectorized memory access.
|
||||
/// Used when loading data from D tensors and storing data
|
||||
/// to output tensor.
|
||||
/// @tparam BlkGemmPipeSched The version of blockwise-gemm pipeline scheduler (interwave or
|
||||
/// intrawave).
|
||||
/// @tparam BlkGemmPipelineVer The version of blockwise-gemm pipeline.
|
||||
/// @tparam ComputeTypeA Data type used for A input of hardware matrix-multiplication
|
||||
/// instructions.
|
||||
/// @tparam ComputeTypeB Data type used for B input of hardware matrix-multiplication
|
||||
/// instructions.
|
||||
/// @tparam PermuteA Whether the A input tensor has gridwise-gemm friendly data layout
|
||||
/// in global memory. Currently not supported!
|
||||
/// @tparam PermuteB Whether the B input tensor has gridwise-gemm friendly data layout
|
||||
/// in global memory (pre-shuffled).
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename DsLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
GemmSpecialization GemmSpec,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t KPerBlock,
|
||||
index_t AK1,
|
||||
index_t BK1,
|
||||
index_t MPerWmma,
|
||||
index_t NPerWmma,
|
||||
index_t MRepeat,
|
||||
index_t NRepeat,
|
||||
typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
typename ABlockTransferThreadClusterArrangeOrder,
|
||||
typename ABlockTransferSrcAccessOrder,
|
||||
index_t ABlockTransferSrcVectorDim,
|
||||
index_t ABlockTransferSrcScalarPerVector,
|
||||
index_t ABlockTransferDstScalarPerVector_AK1,
|
||||
bool ABlockLdsExtraM,
|
||||
typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
typename BBlockTransferThreadClusterArrangeOrder,
|
||||
typename BBlockTransferSrcAccessOrder,
|
||||
index_t BBlockTransferSrcVectorDim,
|
||||
index_t BBlockTransferSrcScalarPerVector,
|
||||
index_t BBlockTransferDstScalarPerVector_BK1,
|
||||
bool BBlockLdsExtraN,
|
||||
index_t CShuffleMRepeatPerShuffle,
|
||||
index_t CShuffleNRepeatPerShuffle,
|
||||
typename CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlockGemmPipelineScheduler BlkGemmPipeSched = BlockGemmPipelineScheduler::Intrawave,
|
||||
BlockGemmPipelineVersion BlkGemmPipelineVer = BlockGemmPipelineVersion::v1,
|
||||
typename ComputeTypeA = EDataType,
|
||||
typename ComputeTypeB = ComputeTypeA,
|
||||
bool PermuteA = false,
|
||||
bool PermuteB = false>
|
||||
struct DeviceGemmMultipleD_Wmma_CShuffleV3
|
||||
: public DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation>
|
||||
{
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
using GridwiseGemm = GridwiseGemm_wmma_cshuffle_v3<
|
||||
ALayout,
|
||||
BLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
GemmSpec,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
AK1,
|
||||
BK1,
|
||||
MPerWmma,
|
||||
NPerWmma,
|
||||
MRepeat,
|
||||
NRepeat,
|
||||
ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
ABlockTransferThreadClusterArrangeOrder,
|
||||
ABlockTransferSrcAccessOrder,
|
||||
ABlockTransferSrcVectorDim,
|
||||
ABlockTransferSrcScalarPerVector,
|
||||
ABlockTransferDstScalarPerVector_AK1,
|
||||
false,
|
||||
ABlockLdsExtraM,
|
||||
BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
BBlockTransferThreadClusterArrangeOrder,
|
||||
BBlockTransferSrcAccessOrder,
|
||||
BBlockTransferSrcVectorDim,
|
||||
BBlockTransferSrcScalarPerVector,
|
||||
BBlockTransferDstScalarPerVector_BK1,
|
||||
false,
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB,
|
||||
PermuteA,
|
||||
PermuteB>;
|
||||
|
||||
using Argument = typename GridwiseGemm::Argument;
|
||||
|
||||
using DeviceGemmCommon =
|
||||
DeviceGemm_Wmma_CShuffleV3_Common<GridwiseGemm,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
BlockSize,
|
||||
AK1,
|
||||
BK1,
|
||||
GemmSpec,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB>;
|
||||
|
||||
// Invoker
|
||||
using Invoker = typename DeviceGemmCommon::Invoker;
|
||||
|
||||
static bool IsSupportedArgument(const Argument& arg)
|
||||
{
|
||||
return DeviceGemmCommon::IsSupportedArgument(arg);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
|
||||
static auto MakeArgument(const void* p_a,
|
||||
const void* p_b,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_e,
|
||||
index_t M,
|
||||
index_t N,
|
||||
index_t K,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
std::array<index_t, NumDTensor> StrideDs,
|
||||
index_t StrideE,
|
||||
index_t KBatch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
{
|
||||
return Argument{static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
p_ds,
|
||||
static_cast<EDataType*>(p_e),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideDs,
|
||||
StrideE,
|
||||
KBatch,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(const void* p_a,
|
||||
const void* p_b,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_e,
|
||||
index_t M,
|
||||
index_t N,
|
||||
index_t K,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
std::array<ck::index_t, NumDTensor> StrideDs,
|
||||
index_t StrideE,
|
||||
index_t KBatch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op) override
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
p_ds,
|
||||
static_cast<EDataType*>(p_e),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideDs,
|
||||
StrideE,
|
||||
KBatch,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
std::map<BlockGemmPipelineScheduler, std::string> BlkGemmPipelineSchedulerToString{
|
||||
{BlockGemmPipelineScheduler::Intrawave, "Intrawave"},
|
||||
{BlockGemmPipelineScheduler::Interwave, "Interwave"}};
|
||||
|
||||
std::map<BlockGemmPipelineVersion, std::string> BlkGemmPipelineVersionToString{
|
||||
{BlockGemmPipelineVersion::v1, "v1"},
|
||||
{BlockGemmPipelineVersion::v2, "v2"},
|
||||
{BlockGemmPipelineVersion::v3, "v3"},
|
||||
{BlockGemmPipelineVersion::v4, "v4"},
|
||||
{BlockGemmPipelineVersion::v5, "v5"}};
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceGemmMultipleD_Wmma_CShuffleV3"
|
||||
<< "<"
|
||||
<< getGemmSpecializationString(GemmSpec) << ", "
|
||||
<< std::string(ALayout::name)[0]
|
||||
<< std::string(BLayout::name)[0];
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
|
||||
|
||||
str << std::string(DLayout::name)[0];
|
||||
});
|
||||
str << std::string(ELayout::name)[0]
|
||||
<< ">"
|
||||
<< " BlkSize: "
|
||||
<< BlockSize << ", "
|
||||
<< "BlkTile: "
|
||||
<< MPerBlock << "x" << NPerBlock << "x" << KPerBlock << ", "
|
||||
<< "WaveTile: "
|
||||
<< MPerWmma << "x"<<NPerWmma << ", "
|
||||
<< "WaveMap: "
|
||||
<< MRepeat << "x" << NRepeat << ", "
|
||||
<< "VmemReadVec: "
|
||||
<< ABlockTransferSrcScalarPerVector << "x" << BBlockTransferSrcScalarPerVector << ", "
|
||||
<< "BlkGemmPipelineScheduler: "
|
||||
<< BlkGemmPipelineSchedulerToString[BlkGemmPipeSched] << ", "
|
||||
<< "BlkGemmPipelineVersion: "
|
||||
<< BlkGemmPipelineVersionToString[BlkGemmPipelineVer] << ", "
|
||||
<< "BlkGemmPipelinePrefetchStages: "
|
||||
<< GridwiseGemm::BlockwiseGemmPipe::PrefetchStages << ", "
|
||||
<< "KPack: "
|
||||
<< GridwiseGemm::KPack;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
REGISTER_EXTRA_PRINTING_METHODS
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -177,15 +177,16 @@ struct DeviceGemm_Wmma_CShuffleV3 : public DeviceGemmV2<ALayout,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation>
|
||||
{
|
||||
// GridwiseGemm
|
||||
using GridwiseGemm = GridwiseGemm_wmma_cshuffle_v3<
|
||||
ALayout,
|
||||
BLayout,
|
||||
Tuple<>, // DsLayout
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
Tuple<>, // DsDataType
|
||||
CDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
@@ -220,7 +221,7 @@ struct DeviceGemm_Wmma_CShuffleV3 : public DeviceGemmV2<ALayout,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
Sequence<CShuffleBlockTransferScalarPerVector_NPerBlock>,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -230,21 +231,24 @@ struct DeviceGemm_Wmma_CShuffleV3 : public DeviceGemmV2<ALayout,
|
||||
|
||||
using Argument = typename GridwiseGemm::Argument;
|
||||
|
||||
using DeviceGemmCommon = DeviceGemm_Wmma_CShuffleV3_Common<GridwiseGemm,
|
||||
ADataType,
|
||||
BDataType,
|
||||
CDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
BlockSize,
|
||||
AK1,
|
||||
BK1,
|
||||
GemmSpec,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB>;
|
||||
using DeviceGemmCommon =
|
||||
DeviceGemm_Wmma_CShuffleV3_Common<GridwiseGemm,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Tuple<>,
|
||||
CDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
BlockSize,
|
||||
AK1,
|
||||
BK1,
|
||||
GemmSpec,
|
||||
Sequence<CShuffleBlockTransferScalarPerVector_NPerBlock>,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB>;
|
||||
|
||||
// Invoker
|
||||
using Invoker = typename DeviceGemmCommon::Invoker;
|
||||
@@ -275,11 +279,25 @@ struct DeviceGemm_Wmma_CShuffleV3 : public DeviceGemmV2<ALayout,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
index_t KBatch,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation)
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation cde_element_op)
|
||||
{
|
||||
return Argument{p_a, p_b, p_c, M, N, K, StrideA, StrideB, StrideC, KBatch};
|
||||
return Argument{p_a,
|
||||
p_b,
|
||||
std::array<const void*, 0>{}, // p_ds_grid_
|
||||
p_c,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<index_t, 0>{}, // StrideDs_
|
||||
StrideC,
|
||||
KBatch,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
@@ -295,20 +313,25 @@ struct DeviceGemm_Wmma_CShuffleV3 : public DeviceGemmV2<ALayout,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
index_t KBatch,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation) override
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op) override
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
std::array<const void*, 0>{}, // p_ds_grid_
|
||||
static_cast<CDataType*>(p_c),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<index_t, 0>{}, // StrideDs_
|
||||
StrideC,
|
||||
KBatch);
|
||||
KBatch,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
|
||||
@@ -89,11 +89,13 @@ struct DeviceGemm_BScale_Wmma_CShuffleV3 : public DeviceGemmV2BScale<ALayout,
|
||||
using GridwiseGemm = GridwiseGemm_wmma_cshuffle_v3_b_scale<
|
||||
ALayout,
|
||||
BLayout,
|
||||
Tuple<>, // DsLayout
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
Tuple<>, // DsDataType
|
||||
CDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
@@ -130,7 +132,7 @@ struct DeviceGemm_BScale_Wmma_CShuffleV3 : public DeviceGemmV2BScale<ALayout,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
Sequence<CShuffleBlockTransferScalarPerVector_NPerBlock>,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -140,21 +142,24 @@ struct DeviceGemm_BScale_Wmma_CShuffleV3 : public DeviceGemmV2BScale<ALayout,
|
||||
|
||||
using Argument = typename GridwiseGemm::Argument;
|
||||
|
||||
using DeviceGemmCommon = DeviceGemm_Wmma_CShuffleV3_Common<GridwiseGemm,
|
||||
ADataType,
|
||||
BDataType,
|
||||
CDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
BlockSize,
|
||||
AK1,
|
||||
BK1,
|
||||
GemmSpec,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB>;
|
||||
using DeviceGemmCommon =
|
||||
DeviceGemm_Wmma_CShuffleV3_Common<GridwiseGemm,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Tuple<>,
|
||||
CDataType,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
BlockSize,
|
||||
AK1,
|
||||
BK1,
|
||||
GemmSpec,
|
||||
Sequence<CShuffleBlockTransferScalarPerVector_NPerBlock>,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
ComputeTypeB>;
|
||||
|
||||
// Invoker
|
||||
using Invoker = typename DeviceGemmCommon::Invoker;
|
||||
@@ -188,23 +193,25 @@ struct DeviceGemm_BScale_Wmma_CShuffleV3 : public DeviceGemmV2BScale<ALayout,
|
||||
index_t KBatch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op)
|
||||
CElementwiseOperation cde_element_op)
|
||||
{
|
||||
return Argument{p_a,
|
||||
p_b,
|
||||
std::array<const void*, 0>{}, // p_ds_grid_
|
||||
p_c,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<index_t, 0>{}, // StrideDs_
|
||||
StrideC,
|
||||
StrideScaleB,
|
||||
p_b_scale,
|
||||
KBatch,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op};
|
||||
cde_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
@@ -228,12 +235,14 @@ struct DeviceGemm_BScale_Wmma_CShuffleV3 : public DeviceGemmV2BScale<ALayout,
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
std::array<const void*, 0>{}, // p_ds_grid_
|
||||
static_cast<CDataType*>(p_c),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
std::array<index_t, 0>{}, // StrideDs_
|
||||
StrideC,
|
||||
StrideScaleB,
|
||||
static_cast<const BScaleDataType*>(p_b_scale),
|
||||
|
||||
@@ -24,7 +24,8 @@ namespace device {
|
||||
template <typename GridwiseGemm,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename CDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t KPerBlock,
|
||||
@@ -32,6 +33,7 @@ template <typename GridwiseGemm,
|
||||
index_t AK1,
|
||||
index_t BK1,
|
||||
GemmSpecialization GemmSpec,
|
||||
typename CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlockGemmPipelineScheduler BlkGemmPipeSched,
|
||||
BlockGemmPipelineVersion BlkGemmPipelineVer,
|
||||
typename ComputeTypeA,
|
||||
@@ -95,8 +97,22 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
auto size_b_buffer = b_grid_desc_bk0_n_bk1.GetElementSpaceSize() *
|
||||
sizeof(BDataType) / GridwiseGemm::BPackedSize;
|
||||
|
||||
ck::utility::RotatingMemWrapper<Argument> rotating_mem(
|
||||
arg_, stream_config.rotating_count, size_a_buffer, size_b_buffer);
|
||||
const auto ds_grid_desc_m_n = GridwiseGemm::MakeDsGridDescriptor_M_N(
|
||||
arg_.M, arg_.MPadded, arg_.N, arg_.NPadded, arg_.StrideDs);
|
||||
|
||||
std::array<std::size_t, GridwiseGemm::NumDTensor> size_ds_buffers;
|
||||
static_for<0, GridwiseGemm::NumDTensor, 1>{}([&](auto i) {
|
||||
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
|
||||
size_ds_buffers[i] =
|
||||
ds_grid_desc_m_n[i].GetElementSpaceSize() * sizeof(DDataType);
|
||||
});
|
||||
|
||||
ck::utility::RotatingMemWrapperMultiD<Argument, DsDataType> rotating_mem(
|
||||
arg_,
|
||||
stream_config.rotating_count,
|
||||
size_a_buffer,
|
||||
size_b_buffer,
|
||||
size_ds_buffers);
|
||||
rotating_mem.Print();
|
||||
|
||||
auto run_flush_cache = [&]() {
|
||||
@@ -106,9 +122,9 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
rotating_mem.Next();
|
||||
// clear c mem
|
||||
if(arg_.KBatch > 1)
|
||||
HIP_CHECK_ERROR(hipMemsetAsync(arg_.p_c_grid,
|
||||
HIP_CHECK_ERROR(hipMemsetAsync(arg_.p_e_grid,
|
||||
0,
|
||||
arg_.M * arg_.N * sizeof(CDataType),
|
||||
arg_.M * arg_.N * sizeof(EDataType),
|
||||
stream_config.stream_id_));
|
||||
};
|
||||
|
||||
@@ -124,9 +140,9 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
else
|
||||
{
|
||||
if(arg.KBatch > 1)
|
||||
HIP_CHECK_ERROR(hipMemsetAsync(arg.p_c_grid,
|
||||
HIP_CHECK_ERROR(hipMemsetAsync(arg.p_e_grid,
|
||||
0,
|
||||
arg.M * arg.N * sizeof(CDataType),
|
||||
arg.M * arg.N * sizeof(EDataType),
|
||||
stream_config.stream_id_));
|
||||
|
||||
ave_time = launch_and_time_kernel(
|
||||
@@ -149,6 +165,16 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
}
|
||||
}();
|
||||
|
||||
// ThreadwiseTensorSliceTransfer_v7r3 (used in ThreadGroupTensorSliceTransfer_v7r3) is
|
||||
// currently implemented in such a way that all SrcScalarPerVectors must be the same, so
|
||||
// if one of D matrices is column-major, then all SrcScalarPerVectors must be 1. On the
|
||||
// other hand, Split K for 16-bit outputs uses packed atomics so ScalarPerVectors cannot
|
||||
// be odd.
|
||||
constexpr bool AtomicsImplementationExists =
|
||||
!(std::is_same_v<EDataType, ck::half_t> ||
|
||||
std::is_same_v<EDataType, ck::bhalf_t>) ||
|
||||
(CDEShuffleBlockTransferScalarPerVectors{}[0] % 2 == 0);
|
||||
|
||||
if(has_main_k_block_loop)
|
||||
{
|
||||
// Tail number always full
|
||||
@@ -157,12 +183,15 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
{
|
||||
if(arg.KBatch > 1)
|
||||
{
|
||||
const auto kernel =
|
||||
kernel_gemm_wmma_cshuffle_v3<GridwiseGemm,
|
||||
true,
|
||||
InMemoryDataOperationEnum::AtomicAdd,
|
||||
minimum_occupancy>;
|
||||
Run(kernel);
|
||||
if constexpr(AtomicsImplementationExists)
|
||||
{
|
||||
const auto kernel =
|
||||
kernel_gemm_wmma_cshuffle_v3<GridwiseGemm,
|
||||
true,
|
||||
InMemoryDataOperationEnum::AtomicAdd,
|
||||
minimum_occupancy>;
|
||||
Run(kernel);
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
@@ -186,12 +215,15 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
{
|
||||
if(arg.KBatch > 1)
|
||||
{
|
||||
const auto kernel =
|
||||
kernel_gemm_wmma_cshuffle_v3<GridwiseGemm,
|
||||
false,
|
||||
InMemoryDataOperationEnum::AtomicAdd,
|
||||
minimum_occupancy>;
|
||||
Run(kernel);
|
||||
if constexpr(AtomicsImplementationExists)
|
||||
{
|
||||
const auto kernel =
|
||||
kernel_gemm_wmma_cshuffle_v3<GridwiseGemm,
|
||||
false,
|
||||
InMemoryDataOperationEnum::AtomicAdd,
|
||||
minimum_occupancy>;
|
||||
Run(kernel);
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
@@ -229,8 +261,8 @@ struct DeviceGemm_Wmma_CShuffleV3_Common
|
||||
return false;
|
||||
}
|
||||
|
||||
if constexpr(std::is_same_v<CDataType, ck::half_t> ||
|
||||
std::is_same_v<CDataType, ck::bhalf_t>)
|
||||
if constexpr(std::is_same_v<EDataType, ck::half_t> ||
|
||||
std::is_same_v<EDataType, ck::bhalf_t>)
|
||||
{
|
||||
if(arg.KBatch > 1 && ck::is_gfx11_supported())
|
||||
{
|
||||
|
||||
@@ -47,7 +47,7 @@ struct Add
|
||||
__host__ __device__ constexpr void
|
||||
operator()<half_t>(half_t& y, const float& x0, const half_t& x1) const
|
||||
{
|
||||
y = type_convert<half_t>(x0) + x1;
|
||||
y = x0 + type_convert<float>(x1);
|
||||
};
|
||||
|
||||
template <>
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
#include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
|
||||
#include "ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_wmma_selector.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_v6r1.hpp"
|
||||
#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v7r3.hpp"
|
||||
#include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_wmma_cshuffle_v3_common.hpp"
|
||||
@@ -22,9 +22,10 @@ namespace ck {
|
||||
///
|
||||
/// @par Overview
|
||||
/// This GEMM kernel is carrying out following mathematical equation:
|
||||
/// C{M,N} = C_op(A_op(A{M,K}) * B_op(B{K,N}))
|
||||
/// Where A, B are input tensors and C is the output tensor. The A/B/C_op are
|
||||
/// elementwise operations that could be applied on each tensor respectively.
|
||||
/// E{M,N} = CDE_op(A_op(A{M,K}) * B_op(B{K,N}), Ds{M,N}...)
|
||||
/// Where A, B, Ds are input tensors and E is the output tensor. The A/B are elementwise
|
||||
// operations that could be applied on each tensor respectively. The CDE_op is an
|
||||
// elementwise operation applied to the C and all D tensors.
|
||||
/// The \"universal\" gemm comes with multiple pipelines optimized for different usage
|
||||
/// scenarios. That's why it's called \"universal\". It's universal through it's design
|
||||
/// and versatilty.
|
||||
@@ -36,18 +37,20 @@ namespace ck {
|
||||
///
|
||||
/// @tparam ALayout A tensor data layout.
|
||||
/// @tparam BLayout B tensor data layout.
|
||||
/// @tparam CLayout C tensor data layout.
|
||||
/// @tparam DsLayout D tensors data layouts.
|
||||
/// @tparam ELayout E tensor data layout.
|
||||
/// @tparam ADataType A tensor data type.
|
||||
/// @tparam BDataType B tensor data type.
|
||||
/// @tparam AccDataType The accumulation data type related to the hardware
|
||||
/// matrix-multiplication instruction.
|
||||
/// @tparam CShuffleDataType The data type used to store matrix-multiplication results into
|
||||
/// LDS memory during \"CShuffle\" data layout optimization.
|
||||
/// @tparam CDataType C tensor data type.
|
||||
/// @tparam AElementwiseOperation Elementwise operation applied to the A input tensor elements.
|
||||
/// @tparam BElementwiseOperation Elementwise operation applied to the B input tensor elements.
|
||||
/// @tparam CElementwiseOperation Elementwise operation applied to the C output tensor
|
||||
/// (after GEMM).
|
||||
/// @tparam DsDataType D tensors data types.
|
||||
/// @tparam EDataType E tensor data type.
|
||||
/// @tparam AElementwiseOperation Elementwise operation applied to the A input tensor elements.
|
||||
/// @tparam BElementwiseOperation Elementwise operation applied to the B input tensor elements.
|
||||
/// @tparam CDEElementwiseOperation Elementwise operation applied to the C output tensor (after
|
||||
/// GEMM) and D input tensors.
|
||||
/// @tparam GemmSpec Determines used "padding" version.
|
||||
/// @tparam BlockSize The number of threads within workgroup.
|
||||
/// @tparam MPerBlock The input/output data tile size in the M dimension.
|
||||
@@ -105,11 +108,12 @@ namespace ck {
|
||||
/// @tparam CShuffleNRepeatPerShuffle The number of matrix-multiplication instructions
|
||||
/// results to process per wave per iteration of CShuffle
|
||||
/// in N dimension.
|
||||
/// @tparam CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock The spatial
|
||||
/// @tparam CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock The spatial
|
||||
/// thread distribution used for storing data into output
|
||||
/// tensor across output data layout dimensions.
|
||||
/// @tparam CShuffleBlockTransferScalarPerVector_NPerBlock The size of vectorized memory access.
|
||||
/// Used when storing data to output tensor.
|
||||
/// @tparam CDEShuffleBlockTransferScalarPerVectors The size of vectorized memory access.
|
||||
/// Used when loading data from D tensors and storing data
|
||||
/// to output tensor.
|
||||
/// @tparam BlkGemmPipeSched The version of blockwise-gemm pipeline scheduler (interwave or
|
||||
/// intrawave).
|
||||
/// @tparam BlkGemmPipelineVer The version of blockwise-gemm pipeline.
|
||||
@@ -123,15 +127,17 @@ namespace ck {
|
||||
/// in global memory (pre-shuffled).
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout,
|
||||
typename DsLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename AccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename CDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
tensor_operation::device::GemmSpecialization GemmSpec,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
@@ -161,8 +167,8 @@ template <typename ALayout,
|
||||
index_t BBlockLdsExtraN,
|
||||
index_t CShuffleMRepeatPerShuffle,
|
||||
index_t CShuffleNRepeatPerShuffle,
|
||||
typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
typename CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlockGemmPipelineScheduler BlkGemmPipeSched,
|
||||
BlockGemmPipelineVersion BlkGemmPipelineVer,
|
||||
typename ComputeTypeA,
|
||||
@@ -173,15 +179,17 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
: GridwiseGemm_wmma_cshuffle_v3_base<
|
||||
ALayout,
|
||||
BLayout,
|
||||
CLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
CDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
GemmSpec,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
@@ -211,8 +219,8 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -223,15 +231,17 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
using Base = GridwiseGemm_wmma_cshuffle_v3_base<
|
||||
ALayout,
|
||||
BLayout,
|
||||
CLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
CDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
GemmSpec,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
@@ -261,8 +271,8 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -297,17 +307,22 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
using Base::CalculateNPadded;
|
||||
using Base::MakeAGridDescriptor_AK0_M_AK1;
|
||||
using Base::MakeBGridDescriptor_BK0_N_BK1;
|
||||
using Base::MakeCGridDescriptor_M_N;
|
||||
using Base::MakeDEGridDescriptor_M_N;
|
||||
using Base::MakeDsGridDescriptor_M_N;
|
||||
using Base::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock;
|
||||
|
||||
using Base::GetCShuffleBlockDescriptor_MShRepeat_MPerShRepeat_NShRepeat_NPerShRepeat;
|
||||
|
||||
using Base::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock;
|
||||
using Base::MakeDEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock;
|
||||
|
||||
using ThisThreadBlock = ThisThreadBlock<BlockSize>;
|
||||
|
||||
using Base::GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1;
|
||||
using Base::GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1;
|
||||
|
||||
using Base::NumDTensor;
|
||||
using typename Base::DsGridPointer;
|
||||
|
||||
struct Problem
|
||||
{
|
||||
__host__ Problem(index_t M_,
|
||||
@@ -315,14 +330,16 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
index_t K_,
|
||||
index_t StrideA_,
|
||||
index_t StrideB_,
|
||||
index_t StrideC_,
|
||||
std::array<index_t, NumDTensor> StrideDs_,
|
||||
index_t StrideE_,
|
||||
index_t KBatch_)
|
||||
: M{M_},
|
||||
N{N_},
|
||||
K{K_},
|
||||
StrideA{StrideA_},
|
||||
StrideB{StrideB_},
|
||||
StrideC{StrideC_},
|
||||
StrideDs{StrideDs_},
|
||||
StrideE{StrideE_},
|
||||
KBatch{KBatch_},
|
||||
MPadded{CalculateMPadded(M_)},
|
||||
NPadded{CalculateNPadded(N_)},
|
||||
@@ -338,11 +355,19 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
__host__ void Print() const
|
||||
{
|
||||
std::cout << "problem {" << "M:" << M << ", " << "N:" << N << ", " << "K:" << K << ", "
|
||||
<< "SA:" << StrideA << ", " << "SB:" << StrideB << ", " << "SC:" << StrideC
|
||||
<< ", " << "MP:" << MPadded << ", " << "NP:" << NPadded << ", "
|
||||
<< "KRead:" << KRead << ", " << "KP:" << KPadded << ", " << "AK0:" << AK0
|
||||
<< ", " << "BK0:" << BK0 << ", " << "MBlock: " << MBlock << ", "
|
||||
<< "NBlock: " << NBlock << "}" << std::endl;
|
||||
<< "SA:" << StrideA << ", " << "SB:" << StrideB << ", ";
|
||||
if constexpr(NumDTensor > 0)
|
||||
{
|
||||
std::cout << "SDs: { ";
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
std::cout << StrideDs[i] << (i.value < NumDTensor - 1 ? ", " : "");
|
||||
});
|
||||
std::cout << " }, ";
|
||||
}
|
||||
std::cout << "SE:" << StrideE << ", " << "MP:" << MPadded << ", " << "NP:" << NPadded
|
||||
<< ", " << "KRead:" << KRead << ", " << "KP:" << KPadded << ", "
|
||||
<< "AK0:" << AK0 << ", " << "BK0:" << BK0 << ", " << "MBlock: " << MBlock
|
||||
<< ", " << "NBlock: " << NBlock << "}" << std::endl;
|
||||
}
|
||||
|
||||
index_t M;
|
||||
@@ -350,7 +375,8 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
index_t K;
|
||||
index_t StrideA;
|
||||
index_t StrideB;
|
||||
index_t StrideC;
|
||||
std::array<index_t, NumDTensor> StrideDs;
|
||||
index_t StrideE;
|
||||
index_t KBatch;
|
||||
index_t MPadded;
|
||||
index_t NPadded;
|
||||
@@ -367,21 +393,35 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
{
|
||||
__host__ Argument(const ADataType* p_a_grid_,
|
||||
const BDataType* p_b_grid_,
|
||||
CDataType* p_c_grid_,
|
||||
std::array<const void*, NumDTensor> p_ds_grid_,
|
||||
EDataType* p_e_grid_,
|
||||
index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t StrideA_,
|
||||
index_t StrideB_,
|
||||
index_t StrideC_,
|
||||
std::array<index_t, NumDTensor> StrideDs_,
|
||||
index_t StrideE_,
|
||||
index_t k_batch_,
|
||||
AElementwiseOperation a_element_op_,
|
||||
BElementwiseOperation b_element_op_,
|
||||
CDEElementwiseOperation cde_element_op_,
|
||||
bool is_reduce_ = false)
|
||||
: Problem{M_, N_, K_, StrideA_, StrideB_, StrideC_, k_batch_},
|
||||
: Problem{M_, N_, K_, StrideA_, StrideB_, StrideDs_, StrideE_, k_batch_},
|
||||
p_a_grid{p_a_grid_},
|
||||
p_b_grid{p_b_grid_},
|
||||
p_c_grid{p_c_grid_},
|
||||
p_ds_grid{},
|
||||
p_e_grid{p_e_grid_},
|
||||
a_element_op{a_element_op_},
|
||||
b_element_op{b_element_op_},
|
||||
cde_element_op{cde_element_op_},
|
||||
is_reduce(is_reduce_)
|
||||
{
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
|
||||
|
||||
p_ds_grid(i) = static_cast<const DDataType*>(p_ds_grid_[i]);
|
||||
});
|
||||
}
|
||||
|
||||
__host__ __device__ inline bool IsReduceAdd() const
|
||||
@@ -396,42 +436,49 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
|
||||
const ADataType* p_a_grid;
|
||||
const BDataType* p_b_grid;
|
||||
CDataType* p_c_grid;
|
||||
DsGridPointer p_ds_grid;
|
||||
EDataType* p_e_grid;
|
||||
|
||||
const AElementwiseOperation a_element_op;
|
||||
const BElementwiseOperation b_element_op;
|
||||
const CDEElementwiseOperation cde_element_op;
|
||||
|
||||
// TODO: it can be used with SplitK+reduction but currently only used with SplitK+atomicAdd
|
||||
bool is_reduce;
|
||||
};
|
||||
|
||||
struct SplitKBatchOffset
|
||||
{
|
||||
|
||||
__device__ SplitKBatchOffset(Argument& karg)
|
||||
__device__ SplitKBatchOffset(Argument& karg, index_t k_id)
|
||||
{
|
||||
if constexpr(is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
|
||||
{
|
||||
a_k_split_offset = blockIdx.z * karg.KRead / APackedSize;
|
||||
a_k_split_offset = k_id * karg.KRead / APackedSize;
|
||||
}
|
||||
else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
|
||||
{
|
||||
a_k_split_offset = blockIdx.z * karg.KRead * karg.StrideA;
|
||||
a_k_split_offset = k_id * karg.KRead * karg.StrideA;
|
||||
}
|
||||
|
||||
if constexpr(is_same_v<tensor_layout::gemm::RowMajor, BLayout>)
|
||||
{
|
||||
b_k_split_offset = blockIdx.z * karg.KRead * karg.StrideB;
|
||||
b_k_split_offset = k_id * karg.KRead * karg.StrideB;
|
||||
}
|
||||
else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, BLayout>)
|
||||
{
|
||||
if constexpr(!PermuteB)
|
||||
{
|
||||
b_k_split_offset = blockIdx.z * karg.KRead / BPackedSize;
|
||||
b_k_split_offset = k_id * karg.KRead / BPackedSize;
|
||||
}
|
||||
else
|
||||
{
|
||||
const int k0_offset = karg.KRead * karg.N;
|
||||
b_k_split_offset = blockIdx.z * k0_offset / BPackedSize;
|
||||
b_k_split_offset = k_id * k0_offset / BPackedSize;
|
||||
}
|
||||
}
|
||||
|
||||
if(blockIdx.z < static_cast<uint32_t>(karg.KBatch - 1))
|
||||
if(k_id < karg.KBatch - 1)
|
||||
{
|
||||
karg.K = karg.KRead;
|
||||
}
|
||||
@@ -442,7 +489,7 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
|
||||
if(karg.IsReduceAdd())
|
||||
{
|
||||
c_reduce_offset = blockIdx.z * karg.M * karg.N;
|
||||
c_reduce_offset = k_id * karg.M * karg.N;
|
||||
}
|
||||
else
|
||||
{
|
||||
@@ -465,23 +512,32 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
__device__ static index_t GetKBlockPerScale() { return 1; }
|
||||
|
||||
template <bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
TailNumber TailNum = TailNumber::Odd>
|
||||
InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
TailNumber TailNum>
|
||||
__device__ static void Run(const ADataType* p_a_grid,
|
||||
const BDataType* p_b_grid,
|
||||
CDataType* p_c_grid,
|
||||
DsGridPointer& p_ds_grid,
|
||||
EDataType* p_e_grid,
|
||||
void* p_shared,
|
||||
const Problem& problem)
|
||||
const Problem& problem,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
{
|
||||
const auto a_grid_desc_ak0_m_ak1 = MakeAGridDescriptor_AK0_M_AK1(
|
||||
problem.M, problem.MPadded, problem.K, problem.KPadded, problem.StrideA, problem.AK0);
|
||||
const auto b_grid_desc_bk0_n_bk1 = MakeBGridDescriptor_BK0_N_BK1(
|
||||
problem.K, problem.KPadded, problem.N, problem.NPadded, problem.StrideB, problem.BK0);
|
||||
const auto c_grid_desc_m_n = MakeCGridDescriptor_M_N(
|
||||
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideC);
|
||||
const auto c_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
c_grid_desc_m_n, problem.MBlock, problem.NBlock);
|
||||
const auto ds_grid_desc_m_n = MakeDsGridDescriptor_M_N(
|
||||
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideDs);
|
||||
const auto e_grid_desc_m_n = Base::template MakeDEGridDescriptor_M_N<ELayout>(
|
||||
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideE);
|
||||
const auto ds_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
ds_grid_desc_m_n, problem.MBlock, problem.NBlock);
|
||||
const auto e_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeDEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
e_grid_desc_m_n, problem.MBlock, problem.NBlock);
|
||||
|
||||
// divide block work by [M, N]
|
||||
const auto block_2_ctile_map = Block2CTileMap{problem.M, problem.N, 4};
|
||||
@@ -491,8 +547,8 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
|
||||
if(!block_2_ctile_map.ValidCTileIndex(
|
||||
block_work_idx,
|
||||
make_tuple(c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
|
||||
make_tuple(e_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
|
||||
{
|
||||
return;
|
||||
}
|
||||
@@ -508,17 +564,23 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
|
||||
Base::template Run<decltype(a_grid_desc_ak0_m_ak1),
|
||||
decltype(b_grid_desc_bk0_n_bk1),
|
||||
decltype(c_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(ds_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(e_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(b_scale_struct),
|
||||
HasMainKBlockLoop,
|
||||
CGlobalMemoryDataOperation,
|
||||
EGlobalMemoryDataOperation,
|
||||
TailNum>(p_a_grid,
|
||||
p_b_grid,
|
||||
p_c_grid,
|
||||
p_ds_grid,
|
||||
p_e_grid,
|
||||
p_shared,
|
||||
a_grid_desc_ak0_m_ak1,
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op,
|
||||
block_m_id,
|
||||
block_n_id,
|
||||
num_k_block_per_scale,
|
||||
@@ -528,17 +590,21 @@ struct GridwiseGemm_wmma_cshuffle_v3
|
||||
// Wrapper function to have __global__ function in common
|
||||
// between gemm_universal, b_scale, ab_scale, etc.
|
||||
template <bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
TailNumber TailNum = TailNumber::Odd>
|
||||
InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
TailNumber TailNum>
|
||||
__device__ static void
|
||||
Run(void* p_shared, const SplitKBatchOffset& splitk_batch_offset, const Argument& karg)
|
||||
Run(void* p_shared, const SplitKBatchOffset& splitk_batch_offset, Argument& karg)
|
||||
{
|
||||
Run<HasMainKBlockLoop, CGlobalMemoryDataOperation, TailNum>(
|
||||
Run<HasMainKBlockLoop, EGlobalMemoryDataOperation, TailNum>(
|
||||
karg.p_a_grid + splitk_batch_offset.a_k_split_offset,
|
||||
karg.p_b_grid + splitk_batch_offset.b_k_split_offset,
|
||||
karg.p_c_grid + splitk_batch_offset.c_reduce_offset,
|
||||
karg.p_ds_grid, //; + splitk_batch_offset.c_reduce_offset,
|
||||
karg.p_e_grid + splitk_batch_offset.c_reduce_offset,
|
||||
p_shared,
|
||||
karg);
|
||||
karg,
|
||||
karg.a_element_op,
|
||||
karg.b_element_op,
|
||||
karg.cde_element_op);
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
@@ -20,15 +20,17 @@ namespace ck {
|
||||
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout,
|
||||
typename DsLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename AccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename CDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
tensor_operation::device::GemmSpecialization GemmSpec,
|
||||
index_t BlockSize,
|
||||
index_t ScaleBlockN, // scale N
|
||||
@@ -60,11 +62,11 @@ template <typename ALayout,
|
||||
index_t BBlockLdsExtraN,
|
||||
index_t CShuffleMRepeatPerShuffle,
|
||||
index_t CShuffleNRepeatPerShuffle,
|
||||
typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
typename CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlockGemmPipelineScheduler BlkGemmPipeSched = BlockGemmPipelineScheduler::Intrawave,
|
||||
BlockGemmPipelineVersion BlkGemmPipelineVer = BlockGemmPipelineVersion::v4,
|
||||
typename ComputeTypeA = CDataType,
|
||||
typename ComputeTypeA = EDataType,
|
||||
typename ComputeTypeB = ComputeTypeA,
|
||||
bool PermuteA = false,
|
||||
bool PermuteB = false>
|
||||
@@ -72,15 +74,17 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
: GridwiseGemm_wmma_cshuffle_v3_base<
|
||||
ALayout,
|
||||
BLayout,
|
||||
CLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
CDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
GemmSpec,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
@@ -110,8 +114,8 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -124,15 +128,17 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
using Base = GridwiseGemm_wmma_cshuffle_v3_base<
|
||||
ALayout,
|
||||
BLayout,
|
||||
CLayout,
|
||||
DsLayout,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
CDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
GemmSpec,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
@@ -162,8 +168,8 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMRepeatPerShuffle,
|
||||
CShuffleNRepeatPerShuffle,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlkGemmPipeSched,
|
||||
BlkGemmPipelineVer,
|
||||
ComputeTypeA,
|
||||
@@ -198,17 +204,22 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
using Base::CalculateNPadded;
|
||||
using Base::MakeAGridDescriptor_AK0_M_AK1;
|
||||
using Base::MakeBGridDescriptor_BK0_N_BK1;
|
||||
using Base::MakeCGridDescriptor_M_N;
|
||||
using Base::MakeDEGridDescriptor_M_N;
|
||||
using Base::MakeDsGridDescriptor_M_N;
|
||||
using Base::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock;
|
||||
|
||||
using Base::GetCShuffleBlockDescriptor_MShRepeat_MPerShRepeat_NShRepeat_NPerShRepeat;
|
||||
|
||||
using Base::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock;
|
||||
using Base::MakeDEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock;
|
||||
|
||||
using ThisThreadBlock = ThisThreadBlock<BlockSize>;
|
||||
|
||||
using Base::GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1;
|
||||
using Base::GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1;
|
||||
|
||||
using Base::NumDTensor;
|
||||
using typename Base::DsGridPointer;
|
||||
|
||||
struct Problem
|
||||
{
|
||||
__host__ Problem(index_t M_,
|
||||
@@ -216,7 +227,8 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
index_t K_,
|
||||
index_t StrideA_,
|
||||
index_t StrideB_,
|
||||
index_t StrideC_,
|
||||
std::array<index_t, NumDTensor> StrideDs_,
|
||||
index_t StrideE_,
|
||||
index_t StrideScaleB_,
|
||||
index_t KBatch_)
|
||||
: M{M_},
|
||||
@@ -224,7 +236,8 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
K{K_},
|
||||
StrideA{StrideA_},
|
||||
StrideB{StrideB_},
|
||||
StrideC{StrideC_},
|
||||
StrideDs{StrideDs_},
|
||||
StrideE{StrideE_},
|
||||
StrideScaleB{StrideScaleB_},
|
||||
KBatch{KBatch_},
|
||||
MPadded{CalculateMPadded(M_)},
|
||||
@@ -241,11 +254,20 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
__host__ void Print() const
|
||||
{
|
||||
std::cout << "problem {" << "M:" << M << ", " << "N:" << N << ", " << "K:" << K << ", "
|
||||
<< "SA:" << StrideA << ", " << "SB:" << StrideB << ", " << "SC:" << StrideC
|
||||
<< ", " << "SScaleB:" << StrideScaleB << ", " << "MP:" << MPadded << ", "
|
||||
<< "NP:" << NPadded << ", " << "KRead:" << KRead << ", " << "KP:" << KPadded
|
||||
<< ", " << "AK0:" << AK0 << ", " << "BK0:" << BK0 << ", "
|
||||
<< "MBlock: " << MBlock << ", " << "NBlock: " << NBlock << "}" << std::endl;
|
||||
<< "SA:" << StrideA << ", " << "SB:" << StrideB << ", ";
|
||||
if constexpr(NumDTensor > 0)
|
||||
{
|
||||
std::cout << "SDs: { ";
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
std::cout << StrideDs[i] << (i.value < NumDTensor - 1 ? ", " : "");
|
||||
});
|
||||
std::cout << " }, ";
|
||||
}
|
||||
std::cout << "SE:" << StrideE << ", " << "SScaleB:" << StrideScaleB << ", "
|
||||
<< "MP:" << MPadded << ", " << "NP:" << NPadded << ", " << "KRead:" << KRead
|
||||
<< ", " << "KP:" << KPadded << ", " << "AK0:" << AK0 << ", " << "BK0:" << BK0
|
||||
<< ", " << "MBlock: " << MBlock << ", " << "NBlock: " << NBlock << "}"
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
index_t M;
|
||||
@@ -253,7 +275,8 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
index_t K;
|
||||
index_t StrideA;
|
||||
index_t StrideB;
|
||||
index_t StrideC;
|
||||
std::array<index_t, NumDTensor> StrideDs;
|
||||
index_t StrideE;
|
||||
index_t StrideScaleB;
|
||||
index_t KBatch;
|
||||
index_t MPadded;
|
||||
@@ -271,30 +294,38 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
{
|
||||
__host__ Argument(const ADataType* p_a_grid_,
|
||||
const BDataType* p_b_grid_,
|
||||
CDataType* p_c_grid_,
|
||||
std::array<const void*, NumDTensor> p_ds_grid_,
|
||||
EDataType* p_e_grid_,
|
||||
index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t StrideA_,
|
||||
index_t StrideB_,
|
||||
index_t StrideC_,
|
||||
std::array<index_t, NumDTensor> StrideDs_,
|
||||
index_t StrideE_,
|
||||
index_t StrideScaleB_,
|
||||
const BScaleType* p_b_scale_grid_,
|
||||
index_t k_batch_,
|
||||
AElementwiseOperation a_element_op_,
|
||||
BElementwiseOperation b_element_op_,
|
||||
CElementwiseOperation c_element_op_,
|
||||
CDEElementwiseOperation cde_element_op_,
|
||||
bool is_reduce_ = false)
|
||||
: Problem{M_, N_, K_, StrideA_, StrideB_, StrideC_, StrideScaleB_, k_batch_},
|
||||
: Problem{M_, N_, K_, StrideA_, StrideB_, StrideDs_, StrideE_, StrideScaleB_, k_batch_},
|
||||
p_a_grid{p_a_grid_},
|
||||
p_b_grid{p_b_grid_},
|
||||
p_c_grid{p_c_grid_},
|
||||
p_ds_grid{},
|
||||
p_e_grid{p_e_grid_},
|
||||
p_b_scale_grid{p_b_scale_grid_},
|
||||
a_element_op{a_element_op_},
|
||||
b_element_op{b_element_op_},
|
||||
c_element_op{c_element_op_},
|
||||
cde_element_op{cde_element_op_},
|
||||
is_reduce(is_reduce_)
|
||||
{
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
|
||||
|
||||
p_ds_grid(i) = static_cast<const DDataType*>(p_ds_grid_[i]);
|
||||
});
|
||||
}
|
||||
|
||||
__host__ __device__ inline bool IsReduceAdd() const
|
||||
@@ -309,57 +340,58 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
|
||||
const ADataType* p_a_grid;
|
||||
const BDataType* p_b_grid;
|
||||
CDataType* p_c_grid;
|
||||
DsGridPointer p_ds_grid;
|
||||
EDataType* p_e_grid;
|
||||
|
||||
const BScaleType* p_b_scale_grid;
|
||||
const AElementwiseOperation a_element_op;
|
||||
const BElementwiseOperation b_element_op;
|
||||
const CElementwiseOperation c_element_op;
|
||||
const CDEElementwiseOperation cde_element_op;
|
||||
bool is_reduce;
|
||||
};
|
||||
|
||||
struct SplitKBatchOffset
|
||||
{
|
||||
|
||||
__device__ SplitKBatchOffset(Argument& karg)
|
||||
__device__ SplitKBatchOffset(Argument& karg, index_t k_id)
|
||||
{
|
||||
if constexpr(is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
|
||||
{
|
||||
a_k_split_offset = blockIdx.z * karg.KRead / APackedSize;
|
||||
a_k_split_offset = k_id * karg.KRead / APackedSize;
|
||||
}
|
||||
else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
|
||||
{
|
||||
a_k_split_offset = blockIdx.z * karg.KRead * karg.StrideA;
|
||||
a_k_split_offset = k_id * karg.KRead * karg.StrideA;
|
||||
}
|
||||
|
||||
if constexpr(is_same_v<tensor_layout::gemm::RowMajor, BLayout>)
|
||||
{
|
||||
b_k_split_offset = blockIdx.z * karg.KRead * karg.StrideB;
|
||||
b_k_split_offset = k_id * karg.KRead * karg.StrideB;
|
||||
}
|
||||
else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, BLayout>)
|
||||
{
|
||||
if constexpr(!PermuteB)
|
||||
{
|
||||
b_k_split_offset = blockIdx.z * karg.KRead / BPackedSize;
|
||||
b_k_split_offset = k_id * karg.KRead / BPackedSize;
|
||||
}
|
||||
else
|
||||
{
|
||||
const int k0_offset = karg.KRead * karg.N;
|
||||
b_k_split_offset = blockIdx.z * k0_offset / BPackedSize;
|
||||
b_k_split_offset = k_id * k0_offset / BPackedSize;
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate B scale offset
|
||||
if constexpr(is_same_v<tensor_layout::gemm::RowMajor, BLayout>)
|
||||
{
|
||||
scale_k_split_offset = blockIdx.z * (karg.KRead / ScaleBlockK) * karg.StrideB;
|
||||
scale_k_split_offset = k_id * (karg.KRead / ScaleBlockK) * karg.StrideB;
|
||||
}
|
||||
else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, BLayout>)
|
||||
{
|
||||
scale_k_split_offset = blockIdx.z * (karg.KRead / ScaleBlockK);
|
||||
scale_k_split_offset = k_id * (karg.KRead / ScaleBlockK);
|
||||
}
|
||||
|
||||
if(blockIdx.z < static_cast<uint32_t>(karg.KBatch - 1))
|
||||
if(k_id < karg.KBatch - 1)
|
||||
{
|
||||
karg.K = karg.KRead;
|
||||
}
|
||||
@@ -370,7 +402,7 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
|
||||
if(karg.IsReduceAdd())
|
||||
{
|
||||
c_reduce_offset = blockIdx.z * karg.M * karg.N;
|
||||
c_reduce_offset = k_id * karg.M * karg.N;
|
||||
}
|
||||
else
|
||||
{
|
||||
@@ -454,24 +486,33 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
}
|
||||
|
||||
template <bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
TailNumber TailNum = TailNumber::Odd>
|
||||
InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
TailNumber TailNum>
|
||||
__device__ static void Run(const ADataType* p_a_grid,
|
||||
const BDataType* p_b_grid,
|
||||
CDataType* p_c_grid,
|
||||
DsGridPointer& p_ds_grid,
|
||||
EDataType* p_e_grid,
|
||||
const BScaleType* p_b_scale_grid,
|
||||
void* p_shared,
|
||||
const Problem& problem)
|
||||
const Problem& problem,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
{
|
||||
const auto a_grid_desc_ak0_m_ak1 = MakeAGridDescriptor_AK0_M_AK1(
|
||||
problem.M, problem.MPadded, problem.K, problem.KPadded, problem.StrideA, problem.AK0);
|
||||
const auto b_grid_desc_bk0_n_bk1 = MakeBGridDescriptor_BK0_N_BK1(
|
||||
problem.K, problem.KPadded, problem.N, problem.NPadded, problem.StrideB, problem.BK0);
|
||||
const auto c_grid_desc_m_n = MakeCGridDescriptor_M_N(
|
||||
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideC);
|
||||
const auto c_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
c_grid_desc_m_n, problem.MBlock, problem.NBlock);
|
||||
const auto ds_grid_desc_m_n = MakeDsGridDescriptor_M_N(
|
||||
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideDs);
|
||||
const auto e_grid_desc_m_n = Base::template MakeDEGridDescriptor_M_N<ELayout>(
|
||||
problem.M, problem.MPadded, problem.N, problem.NPadded, problem.StrideE);
|
||||
const auto ds_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
ds_grid_desc_m_n, problem.MBlock, problem.NBlock);
|
||||
const auto e_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeDEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
e_grid_desc_m_n, problem.MBlock, problem.NBlock);
|
||||
|
||||
// B Scale grid
|
||||
const auto b_scale_grid_desc_bn_ak = make_naive_tensor_descriptor(
|
||||
@@ -487,8 +528,8 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
|
||||
if(!block_2_ctile_map.ValidCTileIndex(
|
||||
block_work_idx,
|
||||
make_tuple(c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
|
||||
make_tuple(e_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
|
||||
{
|
||||
return;
|
||||
}
|
||||
@@ -503,17 +544,23 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
|
||||
Base::template Run<decltype(a_grid_desc_ak0_m_ak1),
|
||||
decltype(b_grid_desc_bk0_n_bk1),
|
||||
decltype(c_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(ds_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(e_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(b_scale_struct),
|
||||
HasMainKBlockLoop,
|
||||
CGlobalMemoryDataOperation,
|
||||
EGlobalMemoryDataOperation,
|
||||
TailNum>(p_a_grid,
|
||||
p_b_grid,
|
||||
p_c_grid,
|
||||
p_ds_grid,
|
||||
p_e_grid,
|
||||
p_shared,
|
||||
a_grid_desc_ak0_m_ak1,
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op,
|
||||
block_m_id,
|
||||
block_n_id,
|
||||
num_k_block_per_scale,
|
||||
@@ -523,18 +570,22 @@ struct GridwiseGemm_wmma_cshuffle_v3_b_scale
|
||||
// NOTE: Wrapper function to have __global__ function in common
|
||||
// between gemm_universal, b_scale, ab_scale, etc.
|
||||
template <bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
TailNumber TailNum = TailNumber::Odd>
|
||||
InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
TailNumber TailNum>
|
||||
__device__ static void
|
||||
Run(void* p_shared, const SplitKBatchOffset& splitk_batch_offset, const Argument& karg)
|
||||
Run(void* p_shared, const SplitKBatchOffset& splitk_batch_offset, Argument& karg)
|
||||
{
|
||||
Run<HasMainKBlockLoop, CGlobalMemoryDataOperation, TailNum>(
|
||||
Run<HasMainKBlockLoop, EGlobalMemoryDataOperation, TailNum>(
|
||||
karg.p_a_grid + splitk_batch_offset.a_k_split_offset,
|
||||
karg.p_b_grid + splitk_batch_offset.b_k_split_offset,
|
||||
karg.p_c_grid + splitk_batch_offset.c_reduce_offset,
|
||||
karg.p_ds_grid, //; + splitk_batch_offset.c_reduce_offset,
|
||||
karg.p_e_grid + splitk_batch_offset.c_reduce_offset,
|
||||
karg.p_b_scale_grid + splitk_batch_offset.scale_k_split_offset,
|
||||
p_shared,
|
||||
karg);
|
||||
karg,
|
||||
karg.a_element_op,
|
||||
karg.b_element_op,
|
||||
karg.cde_element_op);
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
#include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
|
||||
#include "ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_wmma_selector.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_v6r1.hpp"
|
||||
#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v7r3.hpp"
|
||||
#include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
|
||||
@@ -19,7 +19,7 @@ namespace ck {
|
||||
|
||||
template <typename GridwiseGemm,
|
||||
bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
index_t MinimumOccupancy = 1,
|
||||
TailNumber TailNum = TailNumber::Full>
|
||||
__global__ void
|
||||
@@ -31,17 +31,17 @@ __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
|
||||
#if(defined(__gfx11__) || defined(__gfx12__))
|
||||
#if defined(__gfx11__)
|
||||
// gfx11 does not support *_atomic_pk_add_f16/bf16 instructions
|
||||
using c_data_type = remove_cvref_t<remove_pointer_t<decltype(karg.p_c_grid)>>;
|
||||
if constexpr(!(CGlobalMemoryDataOperation == InMemoryDataOperationEnum::AtomicAdd &&
|
||||
(std::is_same_v<c_data_type, ck::half_t> ||
|
||||
std::is_same_v<c_data_type, ck::bhalf_t>)))
|
||||
using e_data_type = remove_cvref_t<remove_pointer_t<decltype(karg.p_e_grid)>>;
|
||||
if constexpr(!(EGlobalMemoryDataOperation == InMemoryDataOperationEnum::AtomicAdd &&
|
||||
(std::is_same_v<e_data_type, ck::half_t> ||
|
||||
std::is_same_v<e_data_type, ck::bhalf_t>)))
|
||||
{
|
||||
#endif
|
||||
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
|
||||
|
||||
auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg);
|
||||
auto splitk_batch_offset = typename GridwiseGemm::SplitKBatchOffset(karg, blockIdx.z);
|
||||
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop, CGlobalMemoryDataOperation, TailNum>(
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop, EGlobalMemoryDataOperation, TailNum>(
|
||||
p_shared, splitk_batch_offset, karg);
|
||||
|
||||
#if defined(__gfx11__)
|
||||
@@ -54,15 +54,17 @@ __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, MinimumOccupancy)
|
||||
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout,
|
||||
typename DsLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename AccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename CDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
tensor_operation::device::GemmSpecialization GemmSpec,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
@@ -92,8 +94,8 @@ template <typename ALayout,
|
||||
index_t BBlockLdsExtraN,
|
||||
index_t CShuffleMRepeatPerShuffle,
|
||||
index_t CShuffleNRepeatPerShuffle,
|
||||
typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
typename CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename CDEShuffleBlockTransferScalarPerVectors,
|
||||
BlockGemmPipelineScheduler BlkGemmPipeSched,
|
||||
BlockGemmPipelineVersion BlkGemmPipelineVer,
|
||||
typename ComputeTypeA,
|
||||
@@ -112,6 +114,9 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
static constexpr auto I6 = Number<6>{};
|
||||
static constexpr auto I7 = Number<7>{};
|
||||
|
||||
static constexpr auto EShuffleBlockTransferScalarPerVector =
|
||||
CDEShuffleBlockTransferScalarPerVectors{}[I0];
|
||||
|
||||
// K1 should be Number<...>
|
||||
static constexpr auto AK0Number = Number<KPerBlock / AK1Value>{};
|
||||
static constexpr auto BK0Number = Number<KPerBlock / BK1Value>{};
|
||||
@@ -430,17 +435,18 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
return MakeWmmaTileDescriptor<NRepeat, NWaves, NPerWmma>(BBlockDesc_BK0_N_BK1{});
|
||||
}
|
||||
|
||||
template <typename DELayout>
|
||||
__host__ __device__ static auto
|
||||
MakeCGridDescriptor_M_N(index_t M, index_t MPad, index_t N, index_t NPad, index_t StrideC)
|
||||
MakeDEGridDescriptor_M_N(index_t M, index_t MPad, index_t N, index_t NPad, index_t StrideDE)
|
||||
{
|
||||
const auto c_grid_desc_mraw_nraw = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, DELayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(StrideC, I1));
|
||||
return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(StrideDE, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CLayout>::value)
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, DELayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(I1, StrideC));
|
||||
return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(I1, StrideDE));
|
||||
}
|
||||
}();
|
||||
|
||||
@@ -493,6 +499,44 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
#endif
|
||||
}
|
||||
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
static constexpr auto MakeDsGridPointer()
|
||||
{
|
||||
return generate_tuple(
|
||||
[&](auto i) {
|
||||
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
|
||||
|
||||
return static_cast<const DDataType*>(nullptr);
|
||||
},
|
||||
Number<NumDTensor>{});
|
||||
}
|
||||
|
||||
using DsGridPointer = decltype(MakeDsGridPointer());
|
||||
|
||||
__host__ __device__ static auto MakeDsGridDescriptor_M_N(
|
||||
index_t M, index_t MPad, index_t N, index_t NPad, std::array<index_t, NumDTensor> StrideDs)
|
||||
{
|
||||
return generate_tuple(
|
||||
[&](auto i) {
|
||||
using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
|
||||
return MakeDEGridDescriptor_M_N<DLayout>(M, MPad, N, NPad, StrideDs[i]);
|
||||
},
|
||||
Number<NumDTensor>{});
|
||||
}
|
||||
|
||||
template <typename DsGridDesc>
|
||||
__device__ static constexpr auto MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
const DsGridDesc& ds_grid_desc_m_n, index_t MBlock, index_t NBlock)
|
||||
{
|
||||
return generate_tuple(
|
||||
[&](auto i) {
|
||||
return MakeDEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
ds_grid_desc_m_n[i], MBlock, NBlock);
|
||||
},
|
||||
Number<NumDTensor>{});
|
||||
}
|
||||
|
||||
__device__ static constexpr auto GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1()
|
||||
{
|
||||
// A matrix in LDS memory, dst of blockwise copy
|
||||
@@ -805,18 +849,18 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
NRepeat,
|
||||
KPack>())>;
|
||||
|
||||
template <typename CGridDesc>
|
||||
__host__ __device__ static constexpr auto MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
const CGridDesc& c_grid_desc_m_n, index_t MBlock, index_t NBlock)
|
||||
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)
|
||||
{
|
||||
const auto c_grid_desc_mblock_mperblock_nblock_nperblock = transform_tensor_descriptor(
|
||||
c_grid_desc_m_n,
|
||||
const auto de_grid_desc_mblock_mperblock_nblock_nperblock = transform_tensor_descriptor(
|
||||
de_grid_desc_m_n,
|
||||
make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{})),
|
||||
make_unmerge_transform(make_tuple(NBlock, Number<NPerBlock>{}))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
|
||||
|
||||
return c_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
return de_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
}
|
||||
|
||||
// block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
|
||||
@@ -950,56 +994,51 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
}
|
||||
}
|
||||
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, ELayout>::value)
|
||||
{
|
||||
if(karg.N % CShuffleBlockTransferScalarPerVector_NPerBlock != 0)
|
||||
if(karg.N % EShuffleBlockTransferScalarPerVector != 0)
|
||||
{
|
||||
if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
|
||||
{
|
||||
std::cout << "Arg N (" << karg.N
|
||||
<< ") value is not a multiple of "
|
||||
"CShuffleBlockTransferScalarPerVector_NPerBlock ("
|
||||
<< CShuffleBlockTransferScalarPerVector_NPerBlock << " )! "
|
||||
<< __FILE__ << ":" << __LINE__ << ", in function: " << __func__
|
||||
<< std::endl;
|
||||
"EShuffleBlockTransferScalarPerVector ("
|
||||
<< EShuffleBlockTransferScalarPerVector << " )! " << __FILE__ << ":"
|
||||
<< __LINE__ << ", in function: " << __func__ << std::endl;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
if(karg.M % CShuffleBlockTransferScalarPerVector_NPerBlock != 0)
|
||||
if(karg.M % EShuffleBlockTransferScalarPerVector != 0)
|
||||
{
|
||||
if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
|
||||
{
|
||||
std::cout << "Arg M (" << karg.M
|
||||
<< ") value is not a multiple of "
|
||||
"CShuffleBlockTransferScalarPerVector_NPerBlock ("
|
||||
<< CShuffleBlockTransferScalarPerVector_NPerBlock << " )! "
|
||||
<< __FILE__ << ":" << __LINE__ << ", in function: " << __func__
|
||||
<< std::endl;
|
||||
"EShuffleBlockTransferScalarPerVector ("
|
||||
<< EShuffleBlockTransferScalarPerVector << " )! " << __FILE__ << ":"
|
||||
<< __LINE__ << ", in function: " << __func__ << std::endl;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
if constexpr(!(is_same<remove_cvref_t<CDataType>, half_t>::value ||
|
||||
is_same<remove_cvref_t<CDataType>, float>::value ||
|
||||
is_same<remove_cvref_t<CDataType>, bhalf_t>::value ||
|
||||
is_same<remove_cvref_t<CDataType>, int32_t>::value))
|
||||
if constexpr(!(is_same<remove_cvref_t<EDataType>, half_t>::value ||
|
||||
is_same<remove_cvref_t<EDataType>, float>::value ||
|
||||
is_same<remove_cvref_t<EDataType>, bhalf_t>::value ||
|
||||
is_same<remove_cvref_t<EDataType>, int32_t>::value))
|
||||
{
|
||||
if(!karg.IsReduceAdd())
|
||||
if(karg.IsAtomicAdd() && karg.KBatch > 1)
|
||||
{
|
||||
if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
|
||||
{
|
||||
std::cout << " KBatch: " << karg.KBatch << " > 1 is not supported yet"
|
||||
<< __FILE__ << ":" << __LINE__ << ", in function: " << __func__
|
||||
<< std::endl;
|
||||
}
|
||||
if(karg.KBatch > 1)
|
||||
{
|
||||
return false;
|
||||
std::cout << " KBatch: " << karg.KBatch << " > 1 is not supported for this "
|
||||
<< "destination type (EDataType) " << __FILE__ << ":" << __LINE__
|
||||
<< ", in function: " << __func__ << std::endl;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1062,19 +1101,26 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
|
||||
template <typename AGridDesc_AK0_M_K1,
|
||||
typename BGridDesc_BK0_N_K1,
|
||||
typename CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename BScaleStruct,
|
||||
bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
InMemoryDataOperationEnum EGlobalMemoryDataOperation,
|
||||
TailNumber TailNum = TailNumber::Odd>
|
||||
__device__ static void Run(const ADataType* p_a_grid,
|
||||
const BDataType* p_b_grid,
|
||||
CDataType* p_c_grid,
|
||||
DsGridPointer p_ds_grid,
|
||||
EDataType* p_e_grid,
|
||||
void* p_shared,
|
||||
const AGridDesc_AK0_M_K1& a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_K1& b_grid_desc_bk0_n_bk1,
|
||||
const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock&
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
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,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op,
|
||||
const index_t& block_m_id,
|
||||
const index_t& block_n_id,
|
||||
const index_t& num_k_block_per_scale,
|
||||
@@ -1084,12 +1130,15 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
p_a_grid, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
|
||||
const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
p_b_grid, b_grid_desc_bk0_n_bk1.GetElementSpaceSize());
|
||||
auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
const AElementwiseOperation a_element_op{};
|
||||
const BElementwiseOperation b_element_op{};
|
||||
const CElementwiseOperation c_element_op{};
|
||||
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());
|
||||
|
||||
// HACK: this force m/n_block_data_idx_on_grid into SGPR
|
||||
const index_t m_block_data_idx_on_grid =
|
||||
@@ -1330,31 +1379,58 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
m_thread_data_on_block_idx[I3]),
|
||||
ck::tensor_operation::element_wise::PassThrough{}};
|
||||
|
||||
// shuffle: blockwise copy C from LDS to global
|
||||
auto c_shuffle_block_copy_lds_to_global = ThreadGroupTensorSliceTransfer_v6r1<
|
||||
ThisThreadBlock, // ThreadGroup
|
||||
CElementwiseOperation, // ElementwiseOperation,
|
||||
CGlobalMemoryDataOperation, // DstInMemOp,
|
||||
// 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>{}));
|
||||
|
||||
// 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>{}));
|
||||
|
||||
// tuple of starting index of C/Ds blockwise copy
|
||||
const auto idx_c_ds_block_begin = container_concat(
|
||||
make_tuple(make_multi_index(0, 0, 0, 0)),
|
||||
generate_tuple([&](auto) { return make_multi_index(block_m_id, 0, block_n_id, 0); },
|
||||
Number<NumDTensor>{}));
|
||||
|
||||
// blockwise copy which loads C from LDS, D from global, applies elementwise
|
||||
// operation and stores result E to global
|
||||
auto cde_shuffle_block_copy_lds_and_global = ThreadGroupTensorSliceTransfer_v7r3<
|
||||
ThisThreadBlock, // ThreadGroup
|
||||
decltype(container_concat(make_tuple(CShuffleDataType{}), DsDataType{})),
|
||||
Tuple<EDataType>,
|
||||
decltype(c_ds_desc_refs),
|
||||
decltype(tie(e_grid_desc_mblock_mperblock_nblock_nperblock)),
|
||||
CDEElementwiseOperation, // ElementwiseOperation,
|
||||
Sequence<static_cast<index_t>(EGlobalMemoryDataOperation)>, // DstInMemOps,
|
||||
Sequence<1,
|
||||
CShuffleMRepeatPerShuffle * MWave * MPerWmma,
|
||||
1,
|
||||
CShuffleNRepeatPerShuffle * NWave * NPerWmma>, // BlockSliceLengths,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
|
||||
CShuffleDataType, // typename SrcData,
|
||||
CDataType, // typename DstData,
|
||||
decltype(c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat),
|
||||
decltype(c_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
Sequence<0, 1, 2, 3>, // typename DimAccessOrder,
|
||||
3, // index_t VectorDim,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock, // index_t ScalarPerVector,
|
||||
true, // bool ThreadTransferSrcResetCoordinateAfterRun,
|
||||
false> // bool ThreadTransferDstResetCoordinateAfterRun>
|
||||
{c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat,
|
||||
make_multi_index(0, 0, 0, 0),
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
make_multi_index(block_m_id, 0, block_n_id, 0),
|
||||
c_element_op};
|
||||
CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
Sequence<0, 1, 2, 3>, // ThreadClusterArrangeOrder,
|
||||
Sequence<0, 1, 2, 3>, // SrcDimAccessOrder,
|
||||
Sequence<0, 1, 2, 3>, // DstDimAccessOrder,
|
||||
3, // SrcVectorDim,
|
||||
3, // DstVectorDim,
|
||||
CDEShuffleBlockTransferScalarPerVectors, // SrcScalarPerVectors
|
||||
EShuffleBlockTransferScalarPerVector, // DstScalarPerVector
|
||||
sequence_merge_t<
|
||||
Sequence<true>,
|
||||
uniform_sequence_gen_t<NumDTensor,
|
||||
false>>, // ThreadTransferSrcResetCoordinateAfterRunFlags
|
||||
Sequence<false>> // ThreadTransferDstResetCoordinateAfterRunFlags
|
||||
{c_ds_desc_refs,
|
||||
idx_c_ds_block_begin,
|
||||
tie(e_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
make_tuple(make_multi_index(block_m_id, 0, block_n_id, 0)),
|
||||
cde_element_op};
|
||||
|
||||
// space filling curve for local reg & global memory
|
||||
// space filling curve for threadwise C in VGPR
|
||||
@@ -1370,7 +1446,7 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
MAccVgprs>>{};
|
||||
|
||||
// space filling curve for shuffled blockwise C in global mem
|
||||
constexpr auto sfc_c_global =
|
||||
constexpr auto sfc_cde_global =
|
||||
SpaceFillingCurve<Sequence<1, MPerBlock, 1, NPerBlock>,
|
||||
Sequence<0, 2, 1, 3>,
|
||||
Sequence<1,
|
||||
@@ -1380,7 +1456,7 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
|
||||
constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
|
||||
|
||||
static_assert(num_access == sfc_c_global.GetNumOfAccess(), "wrong!");
|
||||
static_assert(num_access == sfc_cde_global.GetNumOfAccess(), "wrong!");
|
||||
|
||||
static_for<0, num_access, 1>{}([&](auto access_id) {
|
||||
// make sure it's safe to write to LDS
|
||||
@@ -1397,20 +1473,26 @@ struct GridwiseGemm_wmma_cshuffle_v3_base
|
||||
// make sure it's safe to read from LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each block copy its data from LDS to global
|
||||
c_shuffle_block_copy_lds_to_global.Run(
|
||||
c_shuffle_block_desc_mshrepeat_mpershrepeat_nshrepeat_npershrepeat,
|
||||
c_shuffle_block_buf,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
c_grid_buf);
|
||||
// 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));
|
||||
|
||||
if constexpr(access_id < num_access - 1)
|
||||
{
|
||||
constexpr auto c_global_step = sfc_c_global.GetForwardStep(access_id);
|
||||
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 C
|
||||
c_shuffle_block_copy_lds_to_global.MoveDstSliceWindow(
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock, c_global_step);
|
||||
// move on E
|
||||
cde_shuffle_block_copy_lds_and_global.MoveDstSliceWindow(
|
||||
tie(e_grid_desc_mblock_mperblock_nblock_nperblock), cde_global_step);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
@@ -165,6 +165,9 @@ struct ThreadwiseTensorSliceTransfer_v7r3
|
||||
|
||||
oob_val = oob_val & is_src_valid;
|
||||
|
||||
// TODO: With column-major matrices this step restricts the transferred tensor slice
|
||||
// to just one element, which consequently prevents using atomic operations if the
|
||||
// matrix data type is on 16 bits.
|
||||
if constexpr(SrcScalarPerVectors{}[i] == 1)
|
||||
{
|
||||
auto data_types = SrcDatas{};
|
||||
|
||||
@@ -270,8 +270,8 @@ struct wmma_type<WmmaInstr::wmma_i32_16x16x16_iu8,
|
||||
class FloatA,
|
||||
class FloatB,
|
||||
class FloatC,
|
||||
bool neg_a = false,
|
||||
bool neg_b = false,
|
||||
bool neg_a = true,
|
||||
bool neg_b = true,
|
||||
bool clamp = false>
|
||||
__device__ void run(const FloatA& a, const FloatB& b, FloatC& reg_c) const
|
||||
{
|
||||
@@ -390,8 +390,8 @@ struct wmma_type<WmmaInstr::wmma_i32_16x16x16_iu8_gfx12,
|
||||
class FloatA,
|
||||
class FloatB,
|
||||
class FloatC,
|
||||
bool neg_a = false,
|
||||
bool neg_b = false,
|
||||
bool neg_a = true,
|
||||
bool neg_b = true,
|
||||
bool clamp = false>
|
||||
__device__ void run(const FloatA& a, const FloatB& b, FloatC& reg_c) const
|
||||
{
|
||||
@@ -793,6 +793,9 @@ struct WmmaGemm
|
||||
"base type couple must be (half, float), (bhalf, float), (half, half), (bhalf, bhalf), "
|
||||
"((f8 or bf8, f8 or bf8), float), (int8, int32) or (int4, int32)!");
|
||||
static_for<0, KPack / wmma_instr.k_per_wmma, 1>{}([&](auto k) {
|
||||
// Integer wmma operators need extra input flags to indicate if the input is signed or
|
||||
// unsigned. At the moment CK supports only signed integer inputs, so these flags are
|
||||
// hardcoded.
|
||||
if constexpr(!TransposeC)
|
||||
{
|
||||
wmma_instr.template run<MPerWmma, NPerWmma>(p_a_wave[k], p_b_wave[k], p_c_thread);
|
||||
|
||||
@@ -54,6 +54,7 @@ using MFMA = ck::tensor_layout::gemm::MFMA;
|
||||
|
||||
using Row_Tuple = ck::Tuple<Row>;
|
||||
using Row_Row_Tuple = ck::Tuple<Row, Row>;
|
||||
using Row_Col_Tuple = ck::Tuple<Row, Col>;
|
||||
|
||||
// Conv layout
|
||||
//
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -16,6 +16,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_add_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -41,8 +42,37 @@ void add_device_gemm_add_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>>&);
|
||||
#endif
|
||||
|
||||
// GEMM + Add +
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>>&);
|
||||
|
||||
void add_device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>>&);
|
||||
#endif
|
||||
|
||||
// GEMM + Add
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
@@ -52,17 +82,91 @@ template <typename ALayout,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>
|
||||
ck::tensor_operation::device::DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with Add at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(CK_ENABLE_BF16)
|
||||
if constexpr(is_same_v<ADataType, ck::bhalf_t> && is_same_v<BDataType, ck::bhalf_t> &&
|
||||
is_same_v<D0DataType, ck::bhalf_t> && is_same_v<EDataType, ck::bhalf_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Add
|
||||
// DeviceGemmMultipleD specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -80,6 +184,7 @@ struct DeviceOperationInstanceFactory<
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#ifdef CK_USE_XDL
|
||||
#if defined(CK_ENABLE_INT8) && defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
@@ -104,10 +209,32 @@ struct DeviceOperationInstanceFactory<
|
||||
}
|
||||
#endif
|
||||
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -11,11 +11,13 @@
|
||||
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -67,8 +69,64 @@ void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>&);
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
// GEMM + Add + Add + FastGelu
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>&);
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>&);
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>&);
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>&);
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
// GEMM + Add + FastGelu
|
||||
// DeviceGemmMultipleDSplitK specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
@@ -79,18 +137,100 @@ template <typename ALayout,
|
||||
typename D0DataType,
|
||||
typename D1DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
|
||||
ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::AddAddFastGelu>>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with AddFastGelu at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
constexpr bool IsAllDRowLayout = is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row>;
|
||||
constexpr bool IsAllDFloat16 =
|
||||
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t>;
|
||||
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<EDataType, half_t> && IsAllDRowLayout && IsAllDFloat16)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Add + Add + FastGelu
|
||||
// DeviceGemmMultipleD specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename D1Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename D1DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -100,47 +240,69 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::AddAddFastGelu>;
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
constexpr bool IsAllDRowLayout = is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row>;
|
||||
constexpr bool IsAllDFloat16 =
|
||||
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t>;
|
||||
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
is_same_v<EDataType, half_t> && IsAllDRowLayout && IsAllDFloat16)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
@@ -150,3 +312,4 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif // CK_ENABLE_FP16
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -16,6 +16,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -93,8 +94,64 @@ void add_device_gemm_add_fastgelu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_in
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>&);
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>&);
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>&);
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>&);
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>&);
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
// GEMM + Add + FastGelu
|
||||
// DeviceGemmMultipleDSplitK specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
@@ -103,18 +160,97 @@ template <typename ALayout,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with AddFastGelu at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Add + FastGelu
|
||||
// DeviceGemmMultipleD specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -132,7 +268,8 @@ struct DeviceOperationInstanceFactory<
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_ENABLE_INT8) && defined(CK_ENABLE_FP16)
|
||||
#if defined(CK_USE_XDL)
|
||||
#if defined(CK_ENABLE_FP16) && defined(CK_ENABLE_INT8)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
@@ -143,7 +280,7 @@ struct DeviceOperationInstanceFactory<
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP16 && CK_ENABLE_INT8
|
||||
|
||||
#if defined(CK_ENABLE_BF16) && defined(CK_ENABLE_INT8)
|
||||
if constexpr(is_same_v<ADataType, bhalf_t> && is_same_v<BDataType, int8_t> &&
|
||||
@@ -156,8 +293,9 @@ struct DeviceOperationInstanceFactory<
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_ENABLE_BF16 && CK_ENABLE_INT8
|
||||
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
@@ -186,6 +324,29 @@ struct DeviceOperationInstanceFactory<
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -19,6 +19,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_add_multiply_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -70,6 +71,145 @@ void add_device_gemm_add_multiply_xdl_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>&);
|
||||
#endif
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>&);
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>&);
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>&);
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>&);
|
||||
#endif
|
||||
|
||||
// GEMM + Add + Multiply
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename D1Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename D1DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleDSplitK<
|
||||
ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::AddMultiply>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::AddMultiply>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#ifdef CK_USE_XDL
|
||||
|
||||
#endif
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Add + Multiply
|
||||
template <typename ALayout,
|
||||
@@ -111,6 +251,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#ifdef CK_USE_XDL
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
@@ -144,6 +285,27 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -16,6 +16,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_add_relu_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -41,6 +42,35 @@ void add_device_gemm_add_relu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instan
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>>&);
|
||||
#endif
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>>&);
|
||||
|
||||
void add_device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>>&);
|
||||
#endif
|
||||
|
||||
// GEMM + Add + Relu
|
||||
template <typename ALayout,
|
||||
@@ -52,17 +82,92 @@ template <typename ALayout,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<
|
||||
ck::tensor_operation::device::DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>
|
||||
ck::tensor_operation::device::DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with AddRelu at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
#if defined(CK_ENABLE_BF16)
|
||||
if constexpr(is_same_v<ADataType, ck::bhalf_t> && is_same_v<BDataType, ck::bhalf_t> &&
|
||||
is_same_v<D0DataType, ck::bhalf_t> && is_same_v<EDataType, ck::bhalf_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Add + Relu
|
||||
// DeviceGemmMultipleD specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -80,6 +185,7 @@ struct DeviceOperationInstanceFactory<
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#ifdef CK_USE_XDL
|
||||
#if defined(CK_ENABLE_INT8) && defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
@@ -106,10 +212,32 @@ struct DeviceOperationInstanceFactory<
|
||||
}
|
||||
#endif
|
||||
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -16,6 +16,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_add_silu_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -41,6 +42,107 @@ void add_device_gemm_add_silu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instan
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>>>&);
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>>>&);
|
||||
|
||||
void add_device_gemm_add_silu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>>>&);
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
// GEMM + Add + Silu
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<
|
||||
ck::tensor_operation::device::DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// no split-k xdl implementations
|
||||
#endif // CL_USE_XDL
|
||||
#if defined(CK_USE_WMMA)
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_ENABLE_FP16
|
||||
#if defined(CK_ENABLE_BF16)
|
||||
if constexpr(is_same_v<ADataType, ck::bhalf_t> && is_same_v<BDataType, ck::bhalf_t> &&
|
||||
is_same_v<D0DataType, ck::bhalf_t> && is_same_v<EDataType, ck::bhalf_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_add_silu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_USE_WMMA
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Add + Silu
|
||||
template <typename ALayout,
|
||||
@@ -78,8 +180,11 @@ struct DeviceOperationInstanceFactory<
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
|
||||
#if defined(CK_ENABLE_INT8) && defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
@@ -105,7 +210,28 @@ struct DeviceOperationInstanceFactory<
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CL_USE_XDL
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
|
||||
#endif // CK_USE_WMMA
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
@@ -16,7 +16,8 @@ namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
#if defined(CK_ENABLE_FP16) && defined(CK_USE_XDL)
|
||||
#if defined(CK_USE_XDL)
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
|
||||
Row,
|
||||
@@ -68,8 +69,11 @@ void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances);
|
||||
#endif
|
||||
#if defined(CK_ENABLE_INT8) && defined(CK_USE_WMMA)
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
#if defined(CK_ENABLE_INT8)
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -121,7 +125,63 @@ void add_device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_nk_mn_mn_instances(
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances);
|
||||
#endif
|
||||
#endif // CK_ENABLE_INT8
|
||||
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances);
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances);
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances);
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances);
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
// GEMM + Bilinear
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
@@ -131,18 +191,95 @@ template <typename ALayout,
|
||||
typename BDataType,
|
||||
typename DDataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
|
||||
ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::Bilinear>>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with AddBilinear at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<DDataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<DLayout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<DLayout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<DLayout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<DLayout, Row> && is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + Bilinear
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename DLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename DDataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -152,14 +289,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
BDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::Bilinear>;
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
#if defined(CK_ENABLE_FP16) && defined(CK_USE_XDL)
|
||||
#if defined(CK_USE_XDL)
|
||||
#if defined(CK_ENABLE_FP16)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<DDataType, half_t> && is_same_v<EDataType, half_t>)
|
||||
{
|
||||
@@ -188,8 +326,31 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#if defined(CK_ENABLE_INT8) && defined(CK_USE_WMMA)
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<DLayout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<DDataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
|
||||
// Bilinear wmma i8 instances are using DeviceGemmMultipleD interface.
|
||||
#if defined(CK_ENABLE_INT8)
|
||||
if constexpr(is_same_v<ADataType, std::int8_t> && is_same_v<BDataType, std::int8_t> &&
|
||||
is_same_v<DDataType, std::int8_t> && is_same_v<EDataType, std::int8_t>)
|
||||
{
|
||||
@@ -214,7 +375,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
add_device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_nk_mn_mn_instances(op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_ENABLE_INT8
|
||||
#endif // CK_USE_WMMA
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -16,6 +16,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -67,6 +68,132 @@ void add_device_gemm_fastgelu_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>&);
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>&);
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>&);
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>&);
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>&);
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
// GEMM + Add + FastGelu
|
||||
// DeviceGemmMultipleDSplitK specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
Empty_Tuple,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Empty_Tuple,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
Empty_Tuple,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Empty_Tuple,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with AddFastGelu at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instances(op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instances(op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// GEMM + FastGelu
|
||||
template <typename ALayout,
|
||||
@@ -75,17 +202,17 @@ template <typename ALayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
Empty_Tuple,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Empty_Tuple,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
Empty_Tuple,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Empty_Tuple,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -103,6 +230,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
{
|
||||
@@ -127,6 +255,28 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
add_device_gemm_fastgelu_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
Empty_Tuple,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
Empty_Tuple,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
@@ -136,4 +286,4 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP16
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -19,6 +19,7 @@ namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
#if defined(CK_USE_XDL)
|
||||
void add_device_gemm_multiply_add_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
|
||||
Row,
|
||||
@@ -71,9 +72,64 @@ void add_device_gemm_multiply_add_xdl_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_m
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>&);
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP8
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#if defined(CK_USE_WMMA)
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>&);
|
||||
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>&);
|
||||
#ifdef CK_USE_WMMA_FP8
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>&);
|
||||
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>&);
|
||||
#endif // CK_USE_WMMA_FP8
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
// GEMM + Multiply + Add
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
@@ -84,18 +140,107 @@ template <typename ALayout,
|
||||
typename D0DataType,
|
||||
typename D1DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
|
||||
ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::MultiplyAdd>>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#ifdef CK_USE_XDL
|
||||
// No XDL instances for DeviceGemmMultipleDSplitK with MultiplyAdd at the moment
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#ifdef CK_USE_WMMA
|
||||
if constexpr(is_same_v<ADataType, F16> && is_same_v<BDataType, F16> &&
|
||||
is_same_v<D0DataType, F16> && is_same_v<D1DataType, F16> &&
|
||||
is_same_v<EDataType, F16>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
#ifdef CK_USE_WMMA_FP8
|
||||
if constexpr(is_same_v<ADataType, F16> && is_same_v<BDataType, F8> &&
|
||||
is_same_v<D0DataType, F32> && is_same_v<D1DataType, F32> &&
|
||||
is_same_v<EDataType, F16>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
is_same_v<ELayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
// DeviceGemmMultipleD specialization
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename D0Layout,
|
||||
typename D1Layout,
|
||||
typename ELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename D0DataType,
|
||||
typename D1DataType,
|
||||
typename EDataType>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>
|
||||
{
|
||||
using DeviceOp = DeviceGemmMultipleD<ALayout,
|
||||
BLayout,
|
||||
@@ -105,17 +250,18 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::MultiplyAdd>;
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
|
||||
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
#ifdef CK_USE_XDL
|
||||
if constexpr(is_same_v<ADataType, F16> && is_same_v<BDataType, F16> &&
|
||||
is_same_v<D0DataType, F16> && is_same_v<D1DataType, F16> &&
|
||||
is_same_v<EDataType, F16>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
@@ -133,10 +279,10 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
}
|
||||
}
|
||||
|
||||
#if defined CK_ENABLE_FP8
|
||||
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, f8_t> &&
|
||||
is_same_v<D0DataType, float> && is_same_v<D1DataType, float> &&
|
||||
is_same_v<EDataType, half_t>)
|
||||
#ifdef CK_ENABLE_FP8
|
||||
if constexpr(is_same_v<ADataType, F16> && is_same_v<BDataType, F8> &&
|
||||
is_same_v<D0DataType, F32> && is_same_v<D1DataType, F32> &&
|
||||
is_same_v<EDataType, F16>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
|
||||
is_same_v<D0Layout, Row> && is_same_v<D1Layout, Row> &&
|
||||
@@ -153,7 +299,29 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP8
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#ifdef CK_USE_WMMA
|
||||
// Reuse DeviceGemmMultipleDSplitK instances
|
||||
using Wrapper = DeviceGemmMultipleDSplitKWrapper<ALayout,
|
||||
BLayout,
|
||||
ck::Tuple<D0Layout, D1Layout>,
|
||||
ELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
ck::Tuple<D0DataType, D1DataType>,
|
||||
EDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>;
|
||||
auto new_op_ptrs =
|
||||
DeviceOperationInstanceFactory<typename Wrapper::DeviceOp>::GetInstances();
|
||||
for(auto& op_ptr : new_op_ptrs)
|
||||
{
|
||||
op_ptrs.emplace_back(std::make_unique<Wrapper>(std::move(op_ptr)));
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
@@ -16,6 +16,7 @@ namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
#ifdef CK_USE_XDL
|
||||
#ifdef CK_ENABLE_FP8
|
||||
#ifdef CK_ENABLE_BF16
|
||||
void add_device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_comp_default_instances_part1(
|
||||
@@ -199,7 +200,7 @@ void add_device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_mem_v2_kpadding_i
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
#endif
|
||||
#endif // CK_ENABLE_BF16
|
||||
#ifdef CK_ENABLE_FP16
|
||||
void add_device_gemm_multiply_multiply_xdl_f8_f8_f16_mk_nk_mn_comp_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
@@ -278,8 +279,8 @@ void add_device_gemm_multiply_multiply_xdl_f8_f8_f16_mk_nk_mn_mem_v2_kpadding_in
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
#endif
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_ENABLE_FP8
|
||||
|
||||
#ifdef CK_ENABLE_FP16
|
||||
void add_device_gemm_multiply_multiply_xdl_f8_f8_f16_mk_nk_mn_comp_default_instances_part1(
|
||||
@@ -463,7 +464,7 @@ void add_device_gemm_multiply_multiply_xdl_f8_f8_f16_mk_nk_mn_mem_v2_kpadding_in
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP16
|
||||
|
||||
#if(defined(CK_ENABLE_FP16) || defined(CK_ENABLE_INT8))
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_f16_mk_nk_mn_comp_default_instances(
|
||||
@@ -544,7 +545,62 @@ void add_device_gemm_multiply_multiply_xdl_i8_i8_f16_mk_nk_mn_mem_v2_kpadding_in
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP16 || CK_ENABLE_INT8
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#ifdef CK_USE_WMMA
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_f16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_bf16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
F32_F32_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_f16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
F8,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_bf16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
F8,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
template <typename ADataType,
|
||||
typename BDataType,
|
||||
@@ -553,36 +609,35 @@ template <typename ADataType,
|
||||
typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout>
|
||||
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleDSplitK<
|
||||
ALayout,
|
||||
BLayout,
|
||||
Tuple<Row, Col>,
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
CDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::MultiplyMultiply>>
|
||||
struct DeviceOperationInstanceFactory<DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
Tuple<Row, Col>,
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
CDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>
|
||||
{
|
||||
using DeviceOp =
|
||||
DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
Tuple<Row, Col>,
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
CDataType,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::MultiplyMultiply>;
|
||||
using DeviceOp = DeviceGemmMultipleDSplitK<ALayout,
|
||||
BLayout,
|
||||
Tuple<Row, Col>,
|
||||
CLayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
CDataType,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>;
|
||||
|
||||
static auto GetInstances()
|
||||
{
|
||||
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
|
||||
|
||||
#ifdef CK_USE_XDL
|
||||
#ifdef CK_ENABLE_FP8
|
||||
#ifdef CK_ENABLE_BF16
|
||||
if constexpr(is_same_v<ADataType, f8_t> && is_same_v<BDataType, f8_t> &&
|
||||
@@ -624,7 +679,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_ENABLE_BF16
|
||||
#ifdef CK_ENABLE_FP16
|
||||
if constexpr(is_same_v<ADataType, f8_t> && is_same_v<BDataType, f8_t> &&
|
||||
is_same_v<CDataType, half_t>)
|
||||
@@ -665,8 +720,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
#endif // CK_ENABLE_FP16
|
||||
#endif // CK_ENABLE_FP8
|
||||
#if(defined(CK_ENABLE_FP16) || defined(CK_ENABLE_INT8))
|
||||
if constexpr(is_same_v<ADataType, int8_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<CDataType, half_t>)
|
||||
@@ -691,6 +746,51 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#endif // CK_USE_XDL
|
||||
|
||||
#ifdef CK_USE_WMMA
|
||||
if constexpr(is_same_v<ADataType, int8_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<CDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<CLayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_f16_km_nk_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
if constexpr(is_same_v<ADataType, int8_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<CDataType, bhalf_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<CLayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_bf16_km_nk_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
if constexpr(is_same_v<ADataType, f8_t> && is_same_v<BDataType, f8_t> &&
|
||||
is_same_v<CDataType, half_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<CLayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_f16_km_nk_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
if constexpr(is_same_v<ADataType, f8_t> && is_same_v<BDataType, f8_t> &&
|
||||
is_same_v<CDataType, bhalf_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<CLayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_bf16_km_nk_mn_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif // CK_USE_WMMA
|
||||
|
||||
return op_ptrs;
|
||||
}
|
||||
};
|
||||
|
||||
@@ -75,7 +75,7 @@ function(add_instance_library INSTANCE_NAME)
|
||||
endif()
|
||||
# Do not build XDL gemm_universal_f8 or gemm_multiply_multiply_f8 for any targets except gfx94
|
||||
if(NOT CK_USE_FP8_ON_UNSUPPORTED_ARCH)
|
||||
if(NOT INST_TARGETS MATCHES "gfx94" AND NOT INST_TARGETS MATCHES "gfx95" AND source_name MATCHES "gemm_multiply_multiply" AND source_name MATCHES "_f8_")
|
||||
if(NOT INST_TARGETS MATCHES "gfx94|gfx95|gfx12" AND source_name MATCHES "gemm_multiply_multiply" AND source_name MATCHES "_f8_")
|
||||
message(DEBUG "removing gemm_multiply_multiply_f8 instance ${source} ")
|
||||
list(REMOVE_ITEM ARGN "${source}")
|
||||
endif()
|
||||
@@ -117,13 +117,13 @@ function(add_instance_library INSTANCE_NAME)
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx90a:xnack+ gfx90a:xnack- gfx908 gfx90a gfx942 gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
endif()
|
||||
|
||||
#only build the fp8 gemm instances for gfx90a if the build argument is set, otherwise only build for gfx942/gfx950
|
||||
#only build the fp8 gemm instances for gfx90a if the build argument is set, otherwise only build for gfx942/gfx950 and gfx1200/gfx1201
|
||||
if(NOT CK_USE_FP8_ON_UNSUPPORTED_ARCH)
|
||||
if(source_name MATCHES "gemm_xdl_universal" AND source_name MATCHES "f8")
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx90a:xnack+ gfx90a:xnack- gfx908 gfx90a gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
endif()
|
||||
if(source_name MATCHES "gemm_multiply_multiply" AND source_name MATCHES "f8")
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx90a:xnack+ gfx90a:xnack- gfx908 gfx90a gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx90a:xnack+ gfx90a:xnack- gfx908 gfx90a gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx10-3-generic gfx11-generic)
|
||||
endif()
|
||||
if(source_name MATCHES "gemm_universal_preshuffle" AND source_name MATCHES "f8")
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx90a:xnack+ gfx90a:xnack- gfx908 gfx90a gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
@@ -136,7 +136,7 @@ function(add_instance_library INSTANCE_NAME)
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx908 gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
endif()
|
||||
if(source_name MATCHES "gemm_multiply_multiply" AND source_name MATCHES "f8")
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx908 gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx908 gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx10-3-generic gfx11-generic)
|
||||
endif()
|
||||
if(source_name MATCHES "gemm_universal_preshuffle" AND source_name MATCHES "f8")
|
||||
list(REMOVE_ITEM INST_TARGETS gfx900 gfx906 gfx906:xnack- gfx908:xnack- gfx908:xnack+ gfx908 gfx1030 gfx1100 gfx1101 gfx1102 gfx1103 gfx1150 gfx1151 gfx1152 gfx1200 gfx1201 gfx10-3-generic gfx11-generic gfx12-generic)
|
||||
@@ -290,7 +290,7 @@ FOREACH(subdir_path ${dir_list})
|
||||
message(DEBUG "Found xdl, dl, and wmma instances, but none of those meet the target list. Skipping.")
|
||||
set(add_inst 0)
|
||||
endif()
|
||||
if(("${cmake_instance}" MATCHES "gemm_multiply_multiply" AND "${cmake_instance}" MATCHES "_f8_" ) AND (NOT INST_TARGETS MATCHES "gfx94") AND (NOT INST_TARGETS MATCHES "gfx95") AND (NOT CK_USE_FP8_ON_UNSUPPORTED_ARCH))
|
||||
if(("${cmake_instance}" MATCHES "gemm_multiply_multiply" AND "${cmake_instance}" MATCHES "_f8_" ) AND (NOT INST_TARGETS MATCHES "gfx94|gfx95|gfx11|gfx12") AND (NOT CK_USE_FP8_ON_UNSUPPORTED_ARCH))
|
||||
message(DEBUG "Found gemm_multiply_multiply_f8 instances, but gfx94/gfx95 not on the target list. Skipping.")
|
||||
set(add_inst 0)
|
||||
endif()
|
||||
|
||||
@@ -1,5 +1,8 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_add_instance
|
||||
device_gemm_add_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
|
||||
device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
)
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// outout: e[m, n]
|
||||
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
|
||||
using device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,69 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// outout: e[m, n]
|
||||
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
|
||||
using device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, Add, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Add>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,5 +1,10 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_add_add_fastgelu_instance
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
|
||||
device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
|
||||
@@ -0,0 +1,78 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// elementwise(c, d0, d1) = fastgelu(c + d0 + d1)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n], d1[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,80 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// elementwise(c, d0, d1) = fastgelu(c + d0 + d1)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n], d1[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 64, 32, 64, 8, 8, 16, 16, 4, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,83 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// elementwise(c, d0, d1) = fastgelu(c + d0 + d1)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n], d1[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,86 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// elementwise(c, d0, d1) = fastgelu(c + d0 + d1)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n], d1[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddAddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddAddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,9 +1,14 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_add_fastgelu_instance
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp
|
||||
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp
|
||||
device_gemm_add_fastgelu_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
)
|
||||
|
||||
@@ -0,0 +1,77 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0)
|
||||
// elementwise(c, d0) = fastgelu(c + d0)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,79 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0)
|
||||
// elementwise(c, d0) = fastgelu(c + d0)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 64, 32, 64, 8, 8, 16, 16, 4, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,82 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0)
|
||||
// elementwise(c, d0) = fastgelu(c + d0)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,85 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0)
|
||||
// elementwise(c, d0) = fastgelu(c + d0)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k], d0[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddFastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddFastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_fastgelu_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,7 +1,11 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_add_multiply_instance
|
||||
device_gemm_add_multiply_xdl_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_xdl_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
)
|
||||
|
||||
@@ -0,0 +1,73 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_kn_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,75 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 64, 32, 64, 8, 8, 16, 16, 4, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_km_nk_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,78 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,81 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, AddMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_multiply_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,5 +1,8 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_add_relu_instance
|
||||
device_gemm_add_relu_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_relu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
)
|
||||
|
||||
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// outout: e[m, n]
|
||||
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
|
||||
using device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, BF16, BF16, BF16_Tuple, BF16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances<
|
||||
GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_relu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,70 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// outout: e[m, n]
|
||||
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
|
||||
using device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F32, PassThrough, PassThrough, AddRelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddRelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_relu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,5 +1,6 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_add_silu_instance
|
||||
device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_silu_xdl_c_shuffle_f16_i8_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_add_silu_xdl_c_shuffle_bf16_i8_bf16_bf16_mk_kn_mn_mn_instance.cpp
|
||||
)
|
||||
|
||||
@@ -0,0 +1,109 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise((a * b), d0, d1)
|
||||
// outout: e[m, n]
|
||||
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
|
||||
|
||||
template <GemmSpecialization GemmSpec, typename T_dataType, typename T_tupleDataType>
|
||||
using device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, T_dataType, T_dataType, T_tupleDataType, T_dataType, F32, F32, PassThrough, PassThrough, AddSilu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmDefault,
|
||||
F16,
|
||||
F16_Tuple>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmMNKPadding,
|
||||
F16,
|
||||
F16_Tuple>{});
|
||||
}
|
||||
|
||||
// implement bf16 with same parameters to avoid duplication
|
||||
void add_device_gemm_add_silu_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
BF16,
|
||||
BF16,
|
||||
BF16_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
AddSilu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmDefault,
|
||||
BF16,
|
||||
BF16_Tuple>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_add_silu_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmMNKPadding,
|
||||
BF16,
|
||||
BF16_Tuple>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -4,6 +4,10 @@ add_instance_library(device_gemm_bilinear_instance
|
||||
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_kn_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_nk_mn_mn_instance.cpp
|
||||
device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_kn_mn_mn_instance.cpp
|
||||
|
||||
@@ -0,0 +1,72 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e[m, n] = bilinear(a[k, m] * b[k, n], d[m, n])
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_kn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,74 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e[m, n] = bilinear(a[k, m] * b[k, n], d[m, n])
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 64, 32, 64, 8, 8, 16, 16, 4, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,77 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e[m, n] = bilinear(a[k, m] * b[k, n], d[m, n])
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,80 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e[m, n] = bilinear(a[k, m] * b[k, n], d[m, n])
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Tuple, Row, F16, F16, F16_Tuple, F16, F32, F16, PassThrough, PassThrough, Bilinear, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
Bilinear>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_bilinear_wmma_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instances<
|
||||
GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -45,7 +45,7 @@ using device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instances = st
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmDefault, 1, 256, 128, 128, 64, 16, 16, 16, 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, 16, 16, 1, 1, 2, S<1, 32, 1, 8>, 16>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmDefault, 1, 128, 64, 64, 64, 16, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 2, S<1, 32, 1, 4>, 16>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmDefault, 1, 64, 32, 32, 64, 16, 16, 16, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 2, S<1, 32, 1, 2>, 16>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmDefault, 1, 32, 16, 16, 64, 16, 16, 16, 1, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 16, 1, 2>, 8>,
|
||||
|
||||
// M/N/K padding
|
||||
// N % 16 == 0 && K % 16 == 0
|
||||
//################################| A| B| Ds| E| AData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| GEMM| Prefetch| Block| MPer| NPer| K0Per| K1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
|
||||
@@ -55,7 +55,7 @@ using device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instances = st
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 256, 128, 128, 64, 16, 16, 16, 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, 16, 16, 1, 1, 2, S<1, 32, 1, 8>, 16>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 128, 64, 64, 64, 16, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 2, S<1, 32, 1, 4>, 16>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 64, 32, 32, 64, 16, 16, 16, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 2, S<1, 32, 1, 2>, 16>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 32, 16, 16, 64, 16, 16, 16, 1, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 16, 1, 2>, 8>,
|
||||
|
||||
// M/N/K padding
|
||||
// N % 8 == 0 && K % 8 == 0
|
||||
//################################| A| B| Ds| E| AData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| GEMM| Prefetch| Block| MPer| NPer| K0Per| K1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
|
||||
@@ -65,7 +65,6 @@ using device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instances = st
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 128, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 4>, 8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 64, 32, 32, 64, 8, 16, 16, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 2>, 8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 32, 16, 16, 64, 8, 16, 16, 1, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
|
||||
|
||||
// M/N/K padding
|
||||
// N % 8 == 0 && K % 8 == 0
|
||||
@@ -76,7 +75,6 @@ using device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instances = st
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 256, 128, 128, 32, 4, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, 1, 2, S<1, 32, 1, 8>, 4>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 128, 64, 64, 32, 4, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, 1, 2, S<1, 32, 1, 4>, 4>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 64, 32, 32, 32, 4, 16, 16, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, 1, 2, S<1, 32, 1, 2>, 4>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 32, 16, 16, 32, 4, 16, 16, 1, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, 1, 1, 1, S<1, 16, 1, 2>, 4>,
|
||||
|
||||
// M/N/K padding
|
||||
// N % 1 == 0 && K % 8 == 0
|
||||
@@ -86,8 +84,7 @@ using device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instances = st
|
||||
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 8>, 1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 128, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 4>, 1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 64, 32, 32, 64, 8, 16, 16, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 2>, 1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 32, 16, 16, 64, 8, 16, 16, 1, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<2, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 1>
|
||||
DeviceGemmMultipleD_Wmma_CShuffle< Row, Col, Row_Tuple, Row, I8, I8, I32, I32, I8_Tuple, I8, PassThrough, PassThrough, Bilinear, GemmMNKPadding, 1, 64, 32, 32, 64, 8, 16, 16, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 2>, 1>
|
||||
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
@@ -1,5 +1,10 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_fastgelu_instance
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instance.cpp
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instance.cpp
|
||||
|
||||
device_gemm_fastgelu_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp
|
||||
device_gemm_fastgelu_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp
|
||||
device_gemm_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instance.cpp
|
||||
|
||||
@@ -0,0 +1,75 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise(a * b)
|
||||
// elementwise(c) = fastgelu(c)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instance = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Row,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instance<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_kn_mn_instance<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,77 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise(a * b)
|
||||
// elementwise(c) = fastgelu(c)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Col, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 64, 32, 64, 8, 8, 16, 16, 4, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Col,
|
||||
Col,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_km_nk_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,80 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise(a * b)
|
||||
// elementwise(c) = fastgelu(c)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_kn_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,83 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
// e = elementwise(a * b)
|
||||
// elementwise(c) = fastgelu(c)
|
||||
// output: e[m, n]
|
||||
// input: a[m, k], b[n, k]
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Empty_Tuple, Row, F16, F16, Empty_Tuple, F16, F32, F32, PassThrough, PassThrough, FastGelu, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Empty_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
Empty_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
FastGelu>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_fastgelu_wmma_c_shuffle_f16_f16_f16_mk_nk_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,7 +1,11 @@
|
||||
# ONLY XDL_KERNELS
|
||||
set(GEMM_MULTIPLY_ADD_INSTANCES)
|
||||
list(APPEND GEMM_MULTIPLY_ADD_INSTANCES device_gemm_multiply_add_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instance.cpp)
|
||||
add_instance_library(device_gemm_multiply_add_instance ${GEMM_MULTIPLY_ADD_INSTANCES})
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
add_instance_library(device_gemm_multiply_add_instance
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_xdl_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instance.cpp
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instance.cpp
|
||||
)
|
||||
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
using device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_kn_mn_mn_mn_instances{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,74 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
using device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F16, F16_F16_Tuple, F16, F32, F16, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F16,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f16_f16_f16_f16_mk_nk_mn_mn_mn_instances{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
using device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Row, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 64, 32, 8, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, 1, 1, S<1, 32, 1, 2>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Row,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_kn_mn_mn_mn_instances{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,74 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
|
||||
using device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 64, 80, 64, 8, 8, 16, 16, 1, 5, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 64, 1, 2>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Interwave, V1>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 128, 128, 128, 32, 8, 8, 16, 16, 4, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<8, 8, 8>, Intrawave, V3>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Row_Tuple, Row, F16, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyAdd, GemmMNKPadding, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<8, 8, 8>, Intrawave, V3>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Row_Tuple,
|
||||
Row,
|
||||
F16,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyAdd>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_add_wmma_c_shuffle_f16_f8_f32_f32_f16_mk_nk_mn_mn_mn_instances{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -1,4 +1,4 @@
|
||||
# ONLY XDL_KERNELS
|
||||
# ONLY XDL_AND_WMMA_KERNELS
|
||||
set(GEMM_MULTIPLY_MULTIPLY_INSTANCES)
|
||||
|
||||
list(APPEND GEMM_MULTIPLY_MULTIPLY_INSTANCES
|
||||
@@ -38,6 +38,11 @@ list(APPEND GEMM_MULTIPLY_MULTIPLY_INSTANCES
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_f16/device_gemm_multiply_multiply_xdl_i8_i8_f16_mk_nk_mn_mem_v1_kpadding_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_f16/device_gemm_multiply_multiply_xdl_i8_i8_f16_mk_nk_mn_mem_v2_default_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_f16/device_gemm_multiply_multiply_xdl_i8_i8_f16_mk_nk_mn_mem_v2_kpadding_instance.cpp
|
||||
|
||||
device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_f16_mk_nk_mn.cpp
|
||||
device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_bf16_mk_nk_mn.cpp
|
||||
device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_f16_mk_nk_mn.cpp
|
||||
device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_bf16_mk_nk_mn.cpp
|
||||
)
|
||||
|
||||
set_source_files_properties(device_gemm_multiply_multiply_xdl_f8_f8_bf16/device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_comp_default_instance_part1.cpp PROPERTIES COMPILE_OPTIONS ";-mllvm;-greedy-reverse-local-assignment=1")
|
||||
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <index_t... Is>
|
||||
using S = Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_multiply_multiply_wmma_f8_f8_bf16_mk_nk_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm| Compute| Compute|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, F8, F8>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_bf16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
F8,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances, device_gemm_multiply_multiply_wmma_f8_f8_bf16_mk_nk_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_wmma_f8_f8_bf16_mk_nk_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <index_t... Is>
|
||||
using S = Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_multiply_multiply_wmma_f8_f8_f16_mk_nk_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm| Compute| Compute|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, F8, F8>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_f16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
F8,
|
||||
F8,
|
||||
F32_F32_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances, device_gemm_multiply_multiply_wmma_f8_f8_f16_mk_nk_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_wmma_f8_f8_f16_mk_nk_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <index_t... Is>
|
||||
using S = Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_multiply_multiply_wmma_i8_i8_bf16_mk_nk_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm| Compute| Compute|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, I8, I8>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_bf16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
F32_F32_Tuple,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances, device_gemm_multiply_multiply_wmma_i8_i8_bf16_mk_nk_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_wmma_i8_i8_bf16_mk_nk_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,71 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle_v3.hpp"
|
||||
#include "ck/utility/sequence.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
template <index_t... Is>
|
||||
using S = Sequence<Is...>;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
|
||||
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_multiply_multiply_wmma_i8_i8_f16_mk_nk_mn_instances = std::tuple<
|
||||
// clang-format off
|
||||
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm| Compute| Compute|
|
||||
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
|
||||
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
|
||||
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 160, 64, 8, 8, 16, 16, 2, 5, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
|
||||
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, I8, I8>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_f16_km_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Row_Col_Tuple,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
F16_F16_Tuple,
|
||||
F16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances, device_gemm_multiply_multiply_wmma_i8_i8_f16_mk_nk_mn_instances<GemmDefault>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_wmma_i8_i8_f16_mk_nk_mn_instances<GemmMNKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -33,7 +33,7 @@ template <typename ADataType,
|
||||
typename ELayout>
|
||||
bool profile_gemm_add_fastgelu_impl(int do_verification,
|
||||
int init_method,
|
||||
bool /*do_log*/,
|
||||
bool do_log,
|
||||
bool time_kernel,
|
||||
int M,
|
||||
int N,
|
||||
@@ -213,6 +213,17 @@ bool profile_gemm_add_fastgelu_impl(int do_verification,
|
||||
{
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
if(do_log)
|
||||
{
|
||||
LogRangeAsType<float>(
|
||||
std::cout << "e_m_n_device_result: ", e_m_n_device_result.mData, ",")
|
||||
<< std::endl;
|
||||
|
||||
LogRangeAsType<float>(
|
||||
std::cout << "e_m_n_host_result: ", e_m_n_host_result.mData, ",")
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
pass = pass && ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -35,7 +35,7 @@ template <typename ADataType,
|
||||
typename ELayout>
|
||||
bool profile_gemm_add_multiply_impl(int do_verification,
|
||||
int init_method,
|
||||
bool /*do_log*/,
|
||||
bool do_log,
|
||||
bool time_kernel,
|
||||
int M,
|
||||
int N,
|
||||
@@ -223,6 +223,17 @@ bool profile_gemm_add_multiply_impl(int do_verification,
|
||||
{
|
||||
e_device_buf.FromDevice(e_m_n_device_result.mData.data());
|
||||
|
||||
if(do_log)
|
||||
{
|
||||
LogRangeAsType<float>(
|
||||
std::cout << "e_m_n_device_result: ", e_m_n_device_result.mData, ",")
|
||||
<< std::endl;
|
||||
|
||||
LogRangeAsType<float>(
|
||||
std::cout << "e_m_n_host_result: ", e_m_n_host_result.mData, ",")
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
pass = pass && ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -43,22 +43,16 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
list(APPEND PROFILER_OPS profile_gemm_reduce.cpp)
|
||||
list(APPEND PROFILER_OPS profile_batched_gemm_add_relu_gemm_add.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_add_fastgelu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_fastgelu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_gemm.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_streamk.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_fastgelu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_relu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_silu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_relu_add_layernorm.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_gemm_fixed_nk.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_gemm_fastgelu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_gemm_tile_loop.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_gemm_multiply_tile_loop.cpp)
|
||||
endif()
|
||||
list(APPEND PROFILER_OPS profile_gemm_multiply_add.cpp)
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx9[45]")
|
||||
list(APPEND PROFILER_OPS profile_gemm_multiply_multiply.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_multiply_multiply_wp.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_ab_scale.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_blockscale_wp.cpp)
|
||||
@@ -69,6 +63,7 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
endif()
|
||||
list(APPEND PROFILER_OPS profile_batched_gemm_reduce.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_multiply.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_bias_add_reduce.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_splitk.cpp)
|
||||
list(APPEND PROFILER_OPS profile_batched_gemm_b_scale.cpp)
|
||||
@@ -84,11 +79,14 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
endif()
|
||||
|
||||
if((SUPPORTED_GPU_TARGETS MATCHES "gfx9" AND (DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)) OR
|
||||
(SUPPORTED_GPU_TARGETS MATCHES "gfx1[12]" AND (DTYPES MATCHES "int8" OR NOT DEFINED DTYPES)))
|
||||
(SUPPORTED_GPU_TARGETS MATCHES "gfx1[12]"))
|
||||
list(APPEND PROFILER_OPS profile_gemm_bilinear.cpp)
|
||||
endif()
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx(9[45]|1[12])")
|
||||
list(APPEND PROFILER_OPS profile_gemm_multiply_multiply.cpp)
|
||||
endif()
|
||||
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx11" OR SUPPORTED_GPU_TARGETS MATCHES "gfx12" OR SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx9" OR SUPPORTED_GPU_TARGETS MATCHES "gfx1[12]")
|
||||
list(APPEND PROFILER_OPS profile_gemm_universal.cpp)
|
||||
list(APPEND PROFILER_OPS profile_batched_gemm.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_b_scale.cpp)
|
||||
@@ -97,6 +95,15 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx11" OR SUPPORTED_GPU_TARGETS MATCHES "gfx12
|
||||
list(APPEND PROFILER_OPS profile_grouped_conv_fwd_clamp.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_conv_bwd_data.cpp)
|
||||
list(APPEND PROFILER_OPS profile_grouped_conv_bwd_weight.cpp)
|
||||
if(DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_multiply.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_multiply_add.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_silu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_fastgelu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_fastgelu.cpp)
|
||||
list(APPEND PROFILER_OPS profile_gemm_add_add_fastgelu.cpp)
|
||||
list(APPEND PROFILER_SOURCES profile_gemm_add.cpp)
|
||||
endif()
|
||||
list(APPEND PROFILER_OPS profile_batched_gemm_gemm.cpp)
|
||||
endif()
|
||||
|
||||
@@ -153,23 +160,20 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
endif()
|
||||
if(DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_batched_gemm_gemm_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_add_fastgelu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_fastgelu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_batched_gemm_add_relu_gemm_add_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_gemm_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_streamk_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_fastgelu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_relu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_silu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_relu_add_layernorm_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_gemm_fixed_nk_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_gemm_fastgelu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_gemm_tile_loop_instance)
|
||||
endif()
|
||||
list(APPEND DEVICE_INSTANCES device_batched_gemm_reduce_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_multiply_add_instance)
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx9[45]")
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_multiply_multiply_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_multiply_multiply_wp_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_ab_scale_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_blockscale_wp_instance)
|
||||
@@ -184,6 +188,7 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_universal_reduce_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_universal_streamk_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_multiply_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_reduce_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_bias_add_reduce_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_conv2d_fwd_instance)
|
||||
@@ -205,9 +210,12 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9")
|
||||
endif()
|
||||
|
||||
if((SUPPORTED_GPU_TARGETS MATCHES "gfx9" AND (DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)) OR
|
||||
(SUPPORTED_GPU_TARGETS MATCHES "gfx1[12]" AND (DTYPES MATCHES "int8" OR NOT DEFINED DTYPES)))
|
||||
(SUPPORTED_GPU_TARGETS MATCHES "gfx1[12]" ))
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_bilinear_instance)
|
||||
endif()
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx(9[45]|1[12])")
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_multiply_multiply_instance)
|
||||
endif()
|
||||
|
||||
if(SUPPORTED_GPU_TARGETS MATCHES "gfx9" OR SUPPORTED_GPU_TARGETS MATCHES "gfx1[12]")
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_universal_instance)
|
||||
@@ -218,6 +226,16 @@ if(SUPPORTED_GPU_TARGETS MATCHES "gfx9" OR SUPPORTED_GPU_TARGETS MATCHES "gfx1[1
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_conv3d_bwd_data_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_conv2d_fwd_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_grouped_conv3d_bwd_weight_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_relu_instance)
|
||||
if(DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_multiply_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_multiply_add_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_silu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_fastgelu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_fastgelu_instance)
|
||||
list(APPEND DEVICE_INSTANCES device_gemm_add_add_fastgelu_instance)
|
||||
endif()
|
||||
list(APPEND DEVICE_INSTANCES device_batched_gemm_gemm_instance)
|
||||
endif()
|
||||
|
||||
|
||||
@@ -35,10 +35,10 @@ int profile_gemm_add_multiply(int argc, char* argv[])
|
||||
// clang-format off
|
||||
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
|
||||
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
|
||||
printf("arg3: matrix layout (0: E[m, n] = AddMultiply((A[m, k] * B[k, n] + D0[m, n]) x D1[m, n]);\n");
|
||||
printf(" 1: E[m, n] = AddMultiply((A[m, k] * B[k, n] + D0[m, n]) x D1[m, n]);\n");
|
||||
printf(" 2: E[m, n] = AddMultiply((A[m, k] * B[k, n] + D0[m, n]) x D1[m, n]);\n");
|
||||
printf(" 3: E[m, n] = AddMultiply((A[m, k] * B[k, n] + D0[m, n]) x D1[m, n]))\n");
|
||||
printf("arg3: matrix layout (0: E[m, n] = (A[m, k] * B[k, n] + D0[m, n]) x D1[m, n];\n");
|
||||
printf(" 1: E[m, n] = (A[m, k] * B[n, k] + D0[m, n]) x D1[m, n];\n");
|
||||
printf(" 2: E[m, n] = (A[k, m] * B[k, n] + D0[m, n]) x D1[m, n];\n");
|
||||
printf(" 3: E[m, n] = (A[k, m] * B[n, k] + D0[m, n]) x D1[m, n])\n");
|
||||
printf("arg4: verification (0: no; 1: yes)\n");
|
||||
printf("arg5: initialization (0: no init; 1: integer value; 2: decimal value)\n");
|
||||
printf("arg6: print tensor value (0: no; 1: yes)\n");
|
||||
|
||||
@@ -27,15 +27,17 @@ int profile_gemm_add_silu(int argc, char* argv[])
|
||||
|
||||
enum struct MatrixDataType
|
||||
{
|
||||
F16_INT8_F16_F16, // 0
|
||||
BF16_INT8_BF16_BF16, // 1
|
||||
F16_INT8_F16_F16 = 0,
|
||||
BF16_INT8_BF16_BF16 = 1,
|
||||
F16_F16_F16_F16 = 2,
|
||||
BF16_BF16_BF16_BF16 = 3
|
||||
};
|
||||
|
||||
if(argc != 15)
|
||||
{
|
||||
// clang-format off
|
||||
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
|
||||
printf("arg2: data type (0: f16&i8 1: bf16&i8)\n");
|
||||
printf("arg2: data type (0: f16&i8 1: bf16&i8 2: f16&f16 3: bf16&bf16)\n");
|
||||
printf("arg3: matrix layout (0: E[m, n] = ReLU(A[m, k] * B[k, n] + D0[m, n]);\n");
|
||||
printf(" 1: E[m, n] = ReLU(A[m, k] * B[n, k] + D0[m, n]);\n");
|
||||
printf(" 2: E[m, n] = ReLU(A[k, m] * B[k, n] + D0[m, n]);\n");
|
||||
@@ -128,6 +130,14 @@ int profile_gemm_add_silu(int argc, char* argv[])
|
||||
{
|
||||
return profile(BF16{}, INT8{}, F32{}, BF16{}, BF16{}, Row{}, Row{}, Row{}, Row{});
|
||||
}
|
||||
else if(data_type == MatrixDataType::BF16_BF16_BF16_BF16 && layout == MatrixLayout::MK_KN_MN_MN)
|
||||
{
|
||||
return profile(BF16{}, BF16{}, F32{}, BF16{}, BF16{}, Row{}, Row{}, Row{}, Row{});
|
||||
}
|
||||
else if(data_type == MatrixDataType::F16_F16_F16_F16 && layout == MatrixLayout::MK_KN_MN_MN)
|
||||
{
|
||||
return profile(F16{}, F16{}, F32{}, F16{}, F16{}, Row{}, Row{}, Row{}, Row{});
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "this data_type & layout is not implemented" << std::endl;
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
@@ -92,9 +92,13 @@ int profile_gemm_multiply_multiply(int argc, char* argv[])
|
||||
using F32 = float;
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F16 = ck::half_t;
|
||||
using F8 = ck::f8_t;
|
||||
using I8 = int8_t;
|
||||
using I32 = int;
|
||||
#if defined(CK_USE_XDL) || defined(CK_USE_WMMA_FP8)
|
||||
using F8 = ck::f8_t;
|
||||
#endif
|
||||
#ifdef CK_ENABLE_INT8
|
||||
using I8 = int8_t;
|
||||
using I32 = int;
|
||||
#endif
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
@@ -163,32 +167,31 @@ int profile_gemm_multiply_multiply(int argc, char* argv[])
|
||||
return pass ? 0 : 1;
|
||||
};
|
||||
|
||||
#if defined(CK_USE_XDL) || defined(CK_USE_WMMA_FP8)
|
||||
if(data_type == GemmDataType::F8_F8_BF16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
{
|
||||
return profile(
|
||||
F8{}, F8{}, F8{}, F32{}, F32{}, F32{}, BF16{}, Row{}, Col{}, Row{}, Col{}, Row{});
|
||||
}
|
||||
else if(data_type == GemmDataType::F8_F8_F16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
if(data_type == GemmDataType::F8_F8_F16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
{
|
||||
return profile(
|
||||
F8{}, F8{}, F8{}, F32{}, F32{}, F32{}, F16{}, Row{}, Col{}, Row{}, Col{}, Row{});
|
||||
}
|
||||
else if(data_type == GemmDataType::INT8_INT8_BF16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
#endif // CK_ENABLE_FP8
|
||||
if(data_type == GemmDataType::INT8_INT8_BF16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
{
|
||||
return profile(
|
||||
I8{}, I8{}, I8{}, I32{}, F32{}, F32{}, BF16{}, Row{}, Col{}, Row{}, Col{}, Row{});
|
||||
}
|
||||
else if(data_type == GemmDataType::INT8_INT8_F16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
if(data_type == GemmDataType::INT8_INT8_F16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
{
|
||||
return profile(
|
||||
I8{}, I8{}, I8{}, I32{}, F16{}, F16{}, F16{}, Row{}, Col{}, Row{}, Col{}, Row{});
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "this data_type & layout is not implemented" << std::endl;
|
||||
|
||||
return 1;
|
||||
}
|
||||
std::cout << "this data_type & layout is not implemented" << std::endl;
|
||||
return 1;
|
||||
}
|
||||
|
||||
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_multiply_multiply);
|
||||
|
||||
2
profiler/src/profile_gemm_universal_streamk.cpp
Executable file → Normal file
2
profiler/src/profile_gemm_universal_streamk.cpp
Executable file → Normal file
@@ -1,5 +1,5 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
|
||||
@@ -1,19 +1,71 @@
|
||||
add_gtest_executable(test_gemm_add test_gemm_add_xdl.hpp)
|
||||
# Implements test instances for MultipleD with xdl and wmma support.
|
||||
|
||||
add_gtest_executable(test_gemm_add_xdl test_gemm_add_xdl.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add PRIVATE utility device_gemm_add_instance)
|
||||
target_link_libraries(test_gemm_add_xdl PRIVATE utility device_gemm_add_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_relu test_gemm_add_relu_xdl.cpp)
|
||||
add_gtest_executable(test_gemm_add_relu_xdl test_gemm_add_relu_xdl.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_relu PRIVATE utility device_gemm_add_instance device_gemm_add_relu_instance)
|
||||
target_link_libraries(test_gemm_add_relu_xdl PRIVATE utility device_gemm_add_instance device_gemm_add_relu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_silu test_gemm_add_silu_xdl.cpp)
|
||||
add_gtest_executable(test_gemm_add_silu_xdl test_gemm_add_silu_xdl.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_silu PRIVATE utility device_gemm_add_instance device_gemm_add_silu_instance)
|
||||
target_link_libraries(test_gemm_add_silu_xdl PRIVATE utility device_gemm_add_instance device_gemm_add_silu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_fastgelu test_gemm_add_fastgelu_xdl.cpp)
|
||||
add_gtest_executable(test_gemm_add_silu_wmma test_gemm_add_silu_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_fastgelu PRIVATE utility device_gemm_add_instance device_gemm_add_fastgelu_instance)
|
||||
target_link_libraries(test_gemm_add_silu_wmma PRIVATE utility device_gemm_add_instance device_gemm_add_silu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_fastgelu_xdl test_gemm_add_fastgelu_xdl.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_fastgelu_xdl PRIVATE utility device_gemm_add_instance device_gemm_add_fastgelu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_fastgelu_wmma test_gemm_fastgelu_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_fastgelu_wmma PRIVATE utility device_gemm_fastgelu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_fastgelu_wmma test_gemm_add_fastgelu_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_fastgelu_wmma PRIVATE utility device_gemm_add_fastgelu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_wmma test_gemm_add_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_wmma PRIVATE utility device_gemm_add_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_add_fastgelu_wmma test_gemm_add_add_fastgelu_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_add_fastgelu_wmma PRIVATE utility device_gemm_add_add_fastgelu_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_multiply_multiply_wmma test_gemm_multiply_multiply_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_multiply_multiply_wmma PRIVATE utility device_gemm_multiply_multiply_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_multiply_wmma test_gemm_add_multiply_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_multiply_wmma PRIVATE utility device_gemm_add_multiply_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_multiply_add_wmma test_gemm_multiply_add_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_multiply_add_wmma PRIVATE utility device_gemm_multiply_add_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_bilinear_wmma test_gemm_bilinear_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_bilinear_wmma PRIVATE utility device_gemm_bilinear_instance)
|
||||
endif()
|
||||
|
||||
add_gtest_executable(test_gemm_add_relu_wmma test_gemm_add_relu_wmma.cpp)
|
||||
if(result EQUAL 0)
|
||||
target_link_libraries(test_gemm_add_relu_wmma PRIVATE utility device_gemm_add_relu_instance)
|
||||
endif()
|
||||
39
test/gemm_add/test_gemm_add_add_fastgelu_wmma.cpp
Normal file
39
test/gemm_add/test_gemm_add_add_fastgelu_wmma.cpp
Normal file
@@ -0,0 +1,39 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "gtest/gtest.h"
|
||||
#include "ck/ck.hpp"
|
||||
#include "profiler/profile_gemm_add_add_fastgelu_impl.hpp"
|
||||
#include "test_gemm_common.hpp"
|
||||
|
||||
template <typename Tuple>
|
||||
class TestGemmAddAddFastgelu : public TestGemmD0D1Common<Tuple>
|
||||
{
|
||||
using ProfileCall = typename TestGemmD0D1Common<Tuple>::ProfileCall;
|
||||
|
||||
public:
|
||||
ProfileCall GetImpl() override
|
||||
{
|
||||
return ck::profiler::profile_gemm_add_add_fastgelu_impl<
|
||||
typename TestGemmD0D1Common<Tuple>::ADataType,
|
||||
typename TestGemmD0D1Common<Tuple>::BDataType,
|
||||
typename TestGemmD0D1Common<Tuple>::AccDataType,
|
||||
typename TestGemmD0D1Common<Tuple>::D0DataType,
|
||||
typename TestGemmD0D1Common<Tuple>::D1DataType,
|
||||
typename TestGemmD0D1Common<Tuple>::EDataType,
|
||||
typename TestGemmD0D1Common<Tuple>::ALayout,
|
||||
typename TestGemmD0D1Common<Tuple>::BLayout,
|
||||
typename TestGemmD0D1Common<Tuple>::D0Layout,
|
||||
typename TestGemmD0D1Common<Tuple>::D1Layout,
|
||||
typename TestGemmD0D1Common<Tuple>::ELayout>;
|
||||
}
|
||||
};
|
||||
|
||||
using KernelTypes =
|
||||
::testing::Types<std::tuple<F16, F16, F32, F16, F16, F16, Row, Row, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, F16, Row, Col, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, F16, Col, Row, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, F16, Col, Col, Row, Row, Row>>;
|
||||
|
||||
TYPED_TEST_SUITE(TestGemmAddAddFastgelu, KernelTypes);
|
||||
TYPED_TEST(TestGemmAddAddFastgelu, Test_FP16FP16) { this->Run(); }
|
||||
35
test/gemm_add/test_gemm_add_fastgelu_wmma.cpp
Normal file
35
test/gemm_add/test_gemm_add_fastgelu_wmma.cpp
Normal file
@@ -0,0 +1,35 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "gtest/gtest.h"
|
||||
#include "ck/ck.hpp"
|
||||
#include "profiler/profile_gemm_add_fastgelu_impl.hpp"
|
||||
#include "test_gemm_common.hpp"
|
||||
|
||||
template <typename Tuple>
|
||||
class TestGemmAddFastgelu : public TestGemmD0Common<Tuple>
|
||||
{
|
||||
using ProfileCall = typename TestGemmD0Common<Tuple>::ProfileCall;
|
||||
|
||||
ProfileCall GetImpl() override
|
||||
{
|
||||
return ck::profiler::profile_gemm_add_fastgelu_impl<
|
||||
typename TestGemmD0Common<Tuple>::ADataType,
|
||||
typename TestGemmD0Common<Tuple>::BDataType,
|
||||
typename TestGemmD0Common<Tuple>::AccDataType,
|
||||
typename TestGemmD0Common<Tuple>::D0DataType,
|
||||
typename TestGemmD0Common<Tuple>::EDataType,
|
||||
typename TestGemmD0Common<Tuple>::ALayout,
|
||||
typename TestGemmD0Common<Tuple>::BLayout,
|
||||
typename TestGemmD0Common<Tuple>::D0Layout,
|
||||
typename TestGemmD0Common<Tuple>::ELayout>;
|
||||
}
|
||||
};
|
||||
|
||||
using KernelTypes = ::testing::Types<std::tuple<F16, F16, F32, F16, F16, Row, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, Row, Col, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, Col, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, Col, Col, Row, Row>>;
|
||||
|
||||
TYPED_TEST_SUITE(TestGemmAddFastgelu, KernelTypes);
|
||||
TYPED_TEST(TestGemmAddFastgelu, Test_FP16FP16) { this->Run(); }
|
||||
@@ -1,37 +1,29 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "gtest/gtest.h"
|
||||
#include "ck/ck.hpp"
|
||||
#include "profiler/profile_gemm_add_fastgelu_impl.hpp"
|
||||
#include "test_gemm_add_xdl.hpp"
|
||||
#include "test_gemm_common.hpp"
|
||||
|
||||
template <typename Tuple>
|
||||
class TestGemmAddFastgelu : public TestGemmAdd<Tuple>
|
||||
class TestGemmAddFastgelu : public TestGemmD0Common<Tuple>
|
||||
{
|
||||
private:
|
||||
using ADataType = std::tuple_element_t<0, Tuple>;
|
||||
using BDataType = std::tuple_element_t<1, Tuple>;
|
||||
using AccDataType = std::tuple_element_t<2, Tuple>;
|
||||
using D0DataType = std::tuple_element_t<3, Tuple>;
|
||||
using EDataType = std::tuple_element_t<4, Tuple>;
|
||||
using ALayout = std::tuple_element_t<5, Tuple>;
|
||||
using BLayout = std::tuple_element_t<6, Tuple>;
|
||||
using D0Layout = std::tuple_element_t<7, Tuple>;
|
||||
using ELayout = std::tuple_element_t<8, Tuple>;
|
||||
using ProfileCall = typename TestGemmD0Common<Tuple>::ProfileCall;
|
||||
|
||||
constexpr static auto ProfileGemmAddFastgeluImpl =
|
||||
ck::profiler::profile_gemm_add_fastgelu_impl<ADataType,
|
||||
BDataType,
|
||||
AccDataType,
|
||||
D0DataType,
|
||||
EDataType,
|
||||
ALayout,
|
||||
BLayout,
|
||||
D0Layout,
|
||||
ELayout>;
|
||||
|
||||
decltype(ProfileGemmAddFastgeluImpl) GetImpl() override { return ProfileGemmAddFastgeluImpl; }
|
||||
ProfileCall GetImpl() override
|
||||
{
|
||||
return ck::profiler::profile_gemm_add_fastgelu_impl<
|
||||
typename TestGemmD0Common<Tuple>::ADataType,
|
||||
typename TestGemmD0Common<Tuple>::BDataType,
|
||||
typename TestGemmD0Common<Tuple>::AccDataType,
|
||||
typename TestGemmD0Common<Tuple>::D0DataType,
|
||||
typename TestGemmD0Common<Tuple>::EDataType,
|
||||
typename TestGemmD0Common<Tuple>::ALayout,
|
||||
typename TestGemmD0Common<Tuple>::BLayout,
|
||||
typename TestGemmD0Common<Tuple>::D0Layout,
|
||||
typename TestGemmD0Common<Tuple>::ELayout>;
|
||||
}
|
||||
};
|
||||
|
||||
using KernelTypes = ::testing::Types<std::tuple<F16, I8, F32, F16, F16, Row, Row, Row, Row>,
|
||||
|
||||
39
test/gemm_add/test_gemm_add_multiply_wmma.cpp
Normal file
39
test/gemm_add/test_gemm_add_multiply_wmma.cpp
Normal file
@@ -0,0 +1,39 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "gtest/gtest.h"
|
||||
#include "ck/ck.hpp"
|
||||
#include "test_gemm_common.hpp"
|
||||
#include "profiler/profile_gemm_add_multiply_impl.hpp"
|
||||
|
||||
template <typename Tuple>
|
||||
class TestGemmAddMultiply : public TestGemmD0D1Common<Tuple>
|
||||
{
|
||||
using ProfileCall = typename TestGemmD0D1Common<Tuple>::ProfileCall;
|
||||
|
||||
ProfileCall GetImpl() override
|
||||
{
|
||||
return ck::profiler::profile_gemm_add_multiply_impl<
|
||||
typename TestGemmD0D1Common<Tuple>::ADataType,
|
||||
typename TestGemmD0D1Common<Tuple>::BDataType,
|
||||
typename TestGemmD0D1Common<Tuple>::AccDataType,
|
||||
typename TestGemmD0D1Common<Tuple>::D0DataType,
|
||||
typename TestGemmD0D1Common<Tuple>::D1DataType,
|
||||
typename TestGemmD0D1Common<Tuple>::EDataType,
|
||||
typename TestGemmD0D1Common<Tuple>::ALayout,
|
||||
typename TestGemmD0D1Common<Tuple>::BLayout,
|
||||
typename TestGemmD0D1Common<Tuple>::D0Layout,
|
||||
typename TestGemmD0D1Common<Tuple>::D1Layout,
|
||||
typename TestGemmD0D1Common<Tuple>::ELayout>;
|
||||
}
|
||||
};
|
||||
|
||||
using KernelTypes =
|
||||
::testing::Types<std::tuple<F16, F16, F32, F16, F16, F16, Row, Col, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, F16, Row, Row, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, F16, Col, Col, Row, Row, Row>,
|
||||
std::tuple<F16, F16, F32, F16, F16, F16, Col, Row, Row, Row, Row>>;
|
||||
|
||||
TYPED_TEST_SUITE(TestGemmAddMultiply, KernelTypes);
|
||||
// Due to F16 shuffle data type tests has to run with limited K size. Change instances to FP32?
|
||||
TYPED_TEST(TestGemmAddMultiply, Test) { this->Run({{16, 32, 64}, {2048, 1024, 256}}); }
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user