mirror of
https://github.com/ROCm/composable_kernel.git
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Add basic support for direct loads from global to LDS (#999)
* Add basic support for direct loads from global to LDS
* Clean the code and comments
* Add support for fp16
* Add comments
* Add check for thread cluster lengths
* Align non-direct-load fp16 example
* Small fixes
* Extend IsSupported to check for supported GPU gens
* Build examples only on the supported HW
* Do not throw when instance not supported in 04 example
* Review: Apply review suggestions
* Review: small fix
* Review: small fix
[ROCm/composable_kernel commit: 627054b941]
This commit is contained in:
Bartlomiej Wroblewski
committed by
GitHub
GitHub
parent
b88a739b88
commit
fbbbce4fb4
@@ -13,6 +13,10 @@ list(APPEND GEMM_INSTANCES
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device_gemm_xdl_c_shuffle_f32_f32_f32_mk_nk_mn_instance.cpp
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device_gemm_xdl_c_shuffle_f32_f32_f32_km_kn_mn_instance.cpp
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device_gemm_xdl_c_shuffle_f32_f32_f32_km_nk_mn_instance.cpp
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device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_kn_mn_instance.cpp
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device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_nk_mn_instance.cpp
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device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_kn_mn_instance.cpp
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device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_nk_mn_instance.cpp
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device_gemm_dl_f32_f32_f32_mk_kn_mn_instance.cpp
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device_gemm_dl_f32_f32_f32_mk_nk_mn_instance.cpp
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device_gemm_dl_f32_f32_f32_km_kn_mn_instance.cpp
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@@ -41,6 +45,7 @@ list(APPEND GEMM_INSTANCES
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device_gemm_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp
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device_gemm_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp
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device_gemm_xdl_c_shuffle_2_stage_f16_f16_f16_mk_nk_mn_instance.cpp
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device_gemm_xdl_c_shuffle_lds_direct_load_f16_f16_f16_mk_nk_mn_instance.cpp
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device_gemm_xdl_f16_f16_f16/km_kn_mn_add_instance.cpp
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device_gemm_xdl_f16_f16_f16/km_kn_mn_default_pipeline_v1_instance.cpp
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device_gemm_xdl_f16_f16_f16/km_kn_mn_default_pipeline_v2_instance.cpp
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@@ -0,0 +1,54 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, 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/impl/device_gemm_xdl_cshuffle_lds_direct_load.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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static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
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using device_gemm_xdl_c_shuffle_lds_direct_load_f16_f16_f16_mk_nk_mn_instances = std::tuple<
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// clang-format off
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// ##################################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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// ##################################| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraM| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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// ##################################| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| | | PerVector| | Lengths_K0_N_K1| | | PerVector| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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// ##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Row, Col, Row, F16, F16, F16, F32, F32, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 16, 4>, S<1, 0, 2>, 2, 2, 1, S<4, 16, 4>, S<1, 0, 2>, 2, 2, 1, 1, 1, S<1, 8, 1, 8>, 4>,
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DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Row, Col, Row, F16, F16, F16, F32, F32, PassThrough, PassThrough, PassThrough, GemmMNPadding, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 16, 4>, S<1, 0, 2>, 2, 2, 1, S<4, 16, 4>, S<1, 0, 2>, 2, 2, 1, 1, 1, S<1, 8, 1, 8>, 4>
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// clang-format on
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>;
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void add_device_gemm_xdl_c_shuffle_lds_direct_load_f16_f16_f16_mk_nk_mn_instances(
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std::vector<std::unique_ptr<
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DeviceGemm<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
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instances)
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{
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add_device_operation_instances(
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instances, device_gemm_xdl_c_shuffle_lds_direct_load_f16_f16_f16_mk_nk_mn_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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@@ -0,0 +1,51 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, 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/impl/device_gemm_xdl_cshuffle_lds_direct_load.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 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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using device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_kn_mn_instances = std::tuple<
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// clang-format off
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// ##################################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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// ##################################| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraM| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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// ##################################| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| | | PerVector| | Lengths_K0_N_K1| | | PerVector| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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// ##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Col, Row, Row, F32, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 8, 8>, S<0, 2, 1>, 1, 1, 1, S<4, 8, 8>, S<0, 2, 1>, 1, 1, 1, 1, 1, S<1, 8, 1, 8>, 4>
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// clang-format on
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>;
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void add_device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_kn_mn_instances(
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std::vector<std::unique_ptr<
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DeviceGemm<Col, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
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instances)
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{
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add_device_operation_instances(
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instances, device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_kn_mn_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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@@ -0,0 +1,51 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, 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/impl/device_gemm_xdl_cshuffle_lds_direct_load.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 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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using device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_nk_mn_instances = std::tuple<
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// clang-format off
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// ##################################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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// ##################################| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraM| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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// ##################################| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| | | PerVector| | Lengths_K0_N_K1| | | PerVector| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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// ##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Col, Col, Row, F32, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 8, 8>, S<0, 2, 1>, 1, 1, 1, S<4, 8, 8>, S<1, 0, 2>, 2, 1, 1, 1, 1, S<1, 8, 1, 8>, 4>
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// clang-format on
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>;
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void add_device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_nk_mn_instances(
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std::vector<std::unique_ptr<
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DeviceGemm<Col, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
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instances)
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{
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add_device_operation_instances(
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instances, device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_km_nk_mn_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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@@ -0,0 +1,50 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, 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/impl/device_gemm_xdl_cshuffle_lds_direct_load.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 F32 = float;
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using Row = ck::tensor_layout::gemm::RowMajor;
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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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using device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_kn_mn_instances = std::tuple<
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// clang-format off
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// ##################################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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// ##################################| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraM| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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// ##################################| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| | | PerVector| | Lengths_K0_N_K1| | | PerVector| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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// ##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Row, Row, Row, F32, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 8, 8>, S<1, 0, 2>, 2, 1, 1, S<4, 8, 8>, S<0, 2, 1>, 1, 1, 1, 1, 1, S<1, 8, 1, 8>, 4>
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// clang-format on
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>;
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void add_device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_kn_mn_instances(
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std::vector<std::unique_ptr<
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DeviceGemm<Row, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
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instances)
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{
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add_device_operation_instances(
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instances, device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_kn_mn_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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@@ -0,0 +1,53 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, 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/impl/device_gemm_xdl_cshuffle_lds_direct_load.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 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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static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
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using device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_nk_mn_instances = std::tuple<
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// clang-format off
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// ##################################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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// ##################################| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraM| ThreadCluster| SrcAccessOrder| SrcVectorDim| Scalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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// ##################################| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| | | PerVector| | Lengths_K0_N_K1| | | PerVector| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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// ##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
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DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Row, Col, Row, F32, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 8, 8>, S<1, 0, 2>, 2, 1, 1, S<4, 8, 8>, S<1, 0, 2>, 2, 1, 1, 1, 1, S<1, 8, 1, 8>, 4>,
|
||||
DeviceGemm_Xdl_CShuffle_LdsDirectLoad< Row, Col, Row, F32, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, GemmMNPadding, 1, 256, 64, 64, 32, 8, 8, 32, 32, 1, 1, S<4, 8, 8>, S<1, 0, 2>, 2, 1, 1, S<4, 8, 8>, S<1, 0, 2>, 2, 1, 1, 1, 1, S<1, 8, 1, 8>, 4>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_nk_mn_instances(
|
||||
std::vector<std::unique_ptr<
|
||||
DeviceGemm<Row, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
|
||||
instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances, device_gemm_xdl_c_shuffle_lds_direct_load_f32_f32_f32_mk_nk_mn_instances{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
Reference in New Issue
Block a user