mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-13 09:45:56 +00:00
Fused attention (#345)
* initial stub for gemm_gemm_xdl_cshuffle * set up example code * compiles * prevent integer overflow * harmonize interface between ref_gemm and ref_batched_gemm * batched_gemm_gemm * fix example * host tensor gen: diagonal pattern in lowest two-dimensions only * make c descriptors containing only integral constants * clean up * add BlockwiseGemmXdlops_v2 while exploring an unified approach * implement proper interface * tidy up example * fix compilation warnings * coarsely controlled 2nd gemm padding * remove rocm-cmake's hard requirement for certain revision * clang-format * resolve merge conflict * fix compilation error on gfx10 * adds acc0 elementwise op to interface * attention host validation * add blockwsie softmax v1 * iteratively update softmax+gemm * transpose both gemm0 and gemm1 xdl output so as to avoid broadcasting softmax max/sum * add init method for easier debugging * do away with manual thread cluster calculation * generalize blockwise softmax interface * row-wise softmax sum & max * format * rename to DeviceBatchedGemmSoftmaxGemm * add gemm_softmax_gemm instances and tests * comment Co-authored-by: ltqin <letao.qin@amd.com> Co-authored-by: Chao Liu <chao.liu2@amd.com>
This commit is contained in:
Anthony Chang
@@ -13,6 +13,7 @@ add_subdirectory(gemm_reduce)
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add_subdirectory(gemm_bias_add_reduce)
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add_subdirectory(batched_gemm)
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add_subdirectory(batched_gemm_reduce)
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add_subdirectory(batched_gemm_softmax_gemm)
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add_subdirectory(grouped_gemm)
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add_subdirectory(contraction_scale)
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add_subdirectory(contraction_bilinear)
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@@ -0,0 +1,8 @@
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set(DEVICE_BATCHED_GEMM_SOFTMAX_GEMM_INSTANCE_SOURCE
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device_batched_gemm_softmax_gemm_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gno_gmo_instance.cpp
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)
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add_instance_library(device_batched_gemm_softmax_gemm_instance OBJECT ${DEVICE_BATCHED_GEMM_SOFTMAX_GEMM_INSTANCE_SOURCE})
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target_compile_features(device_batched_gemm_softmax_gemm_instance PUBLIC)
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set_target_properties(device_batched_gemm_softmax_gemm_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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clang_tidy_check(device_batched_gemm_softmax_gemm_instance)
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@@ -0,0 +1,68 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#include <cstdlib>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/device/device_batched_gemm_softmax_gemm_xdl_cshuffle.hpp"
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#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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namespace instance {
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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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template <ck::index_t... Is>
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using S = ck::Sequence<Is...>;
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
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// c[g, m, n] = a[g, m, k] * b[g, n, k]
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using device_batched_gemm_softmax_gemm_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gno_gmo_instances =
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std::tuple<
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// clang-format off
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//#######################################| ALayout| B0Layout| B1Layout| CLayout| AData| B0Data| B1Data| CData| AccData| CShuffle| A| B0| Acc0| B1| C| GEMM| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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//#######################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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//#######################################| | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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//#######################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | |
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DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle< Row, Col, Row, Row, F16, F16, F16, F16, F32, F16, PassThrough, PassThrough, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 256, 128, 32, 128, 32, 8, 8, 2, 32, 32, 2, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S< 8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8>,
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DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle< Row, Col, Row, Row, F16, F16, F16, F16, F32, F16, PassThrough, PassThrough, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 128, 128, 32, 128, 32, 8, 8, 2, 32, 32, 1, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S< 8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8>,
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DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle< Row, Col, Row, Row, F16, F16, F16, F16, F32, F16, PassThrough, PassThrough, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8>,
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DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle< Row, Col, Row, Row, F16, F16, F16, F16, F32, F16, PassThrough, PassThrough, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 128, 64, 32, 128, 32, 8, 8, 2, 32, 32, 1, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S< 8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8>
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// clang-format on
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>;
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void add_device_batched_gemm_softmax_gemm_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gno_gmo_instance(
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std::vector<std::unique_ptr<DeviceBatchedGemmSoftmaxGemm<Row,
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Col,
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Row,
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Row,
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F16,
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F16,
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F16,
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F16,
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PassThrough,
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PassThrough,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances)
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{
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add_device_operation_instances(
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instances,
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device_batched_gemm_softmax_gemm_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gno_gmo_instances{});
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}
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} // namespace instance
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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