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Commit 63b152d6 authored by danyao12's avatar danyao12
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Merge branch 'develop' into ck_tile/fa_bwd_v3

parents ae2d7d2b 14c3cfb1
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example/01_gemm/gemm_dpp_fp16.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -34,6 +34,9 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmDpp ...@@ -34,6 +34,9 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmDpp
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::
ReferenceGemm<ALayout, BLayout, CLayout, ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_wmma_fp16.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -68,6 +68,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmWmma_CShuffle ...@@ -68,6 +68,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmWmma_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_bf16.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -33,6 +33,20 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle ...@@ -33,6 +33,20 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceComputeType = float;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp,
ReferenceComputeType,
ReferenceComputeType>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_bf16_rtn.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -34,6 +34,20 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle ...@@ -34,6 +34,20 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceComputeType = float;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp,
ReferenceComputeType,
ReferenceComputeType>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_fp16.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -47,6 +47,17 @@ using DeviceGemmInstance = DeviceGemmInstance1; ...@@ -47,6 +47,17 @@ using DeviceGemmInstance = DeviceGemmInstance1;
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_fp16_fp8.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -42,6 +42,17 @@ using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataTyp ...@@ -42,6 +42,17 @@ using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataTyp
CElementOp, CElementOp,
ComputeType>; ComputeType>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_fp16_v2.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -46,6 +46,17 @@ using DeviceGemmInstance = ...@@ -46,6 +46,17 @@ using DeviceGemmInstance =
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_fp64.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -41,6 +41,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmXdl ...@@ -41,6 +41,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmXdl
BElementOp, BElementOp,
CElementOp>; CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_fp8.cpp
View file @ 63b152d6
...@@ -37,6 +37,20 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle ...@@ -37,6 +37,20 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceComputeType = float;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp,
ReferenceComputeType,
ReferenceComputeType>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_fp8_bf8.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -44,6 +44,17 @@ using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataTyp ...@@ -44,6 +44,17 @@ using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<ADataTyp
ComputeTypeA, ComputeTypeA,
ComputeTypeB>; ComputeTypeB>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_int8.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -33,6 +33,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle ...@@ -33,6 +33,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_lds_direct_load_fp16.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream> #include <iostream>
...@@ -53,6 +53,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle ...@@ -53,6 +53,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_lds_direct_load_fp32.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream> #include <iostream>
...@@ -52,6 +52,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle ...@@ -52,6 +52,17 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_streamk.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -44,6 +44,17 @@ using DeviceGemmInstance = DeviceGemmStreamK; ...@@ -44,6 +44,17 @@ using DeviceGemmInstance = DeviceGemmStreamK;
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_streamk_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_streamk_example(argc, argv); }
example/01_gemm/gemm_xdl_wavelet_fp16.cpp
View file @ 63b152d6
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp" #include "common.hpp"
...@@ -37,6 +37,17 @@ using DeviceGemmInstance = DeviceGemmInstance; ...@@ -37,6 +37,17 @@ using DeviceGemmInstance = DeviceGemmInstance;
using ReferenceGemmInstance = ck::tensor_operation::host:: using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>; ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
using ReferenceGemmInstanceGPU = ck::tensor_operation::device::ReferenceGemm<ALayout,
BLayout,
CLayout,
ADataType,
BDataType,
CDataType,
AccDataType,
AElementOp,
BElementOp,
CElementOp>;
#include "run_gemm_example.inc" #include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); } int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/run_gemm_example.inc
View file @ 63b152d6
...@@ -173,6 +173,7 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config) ...@@ -173,6 +173,7 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
Tensor<CDataType> c_m_n_host_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{})); Tensor<CDataType> c_m_n_host_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{}));
Tensor<CDataType> c_m_n_device_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{})); Tensor<CDataType> c_m_n_device_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{}));
Tensor<CDataType> c_m_n_device_ref_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{}));
std::cout << "a_m_k: " << a_m_k.mDesc << std::endl; std::cout << "a_m_k: " << a_m_k.mDesc << std::endl;
std::cout << "b_k_n: " << b_k_n.mDesc << std::endl; std::cout << "b_k_n: " << b_k_n.mDesc << std::endl;
...@@ -193,6 +194,8 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config) ...@@ -193,6 +194,8 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
DeviceMem a_m_k_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpaceSize()); DeviceMem a_m_k_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpaceSize());
DeviceMem b_k_n_device_buf(sizeof(BDataType) * b_k_n.mDesc.GetElementSpaceSize()); DeviceMem b_k_n_device_buf(sizeof(BDataType) * b_k_n.mDesc.GetElementSpaceSize());
DeviceMem c_m_n_device_buf(sizeof(CDataType) * c_m_n_device_result.mDesc.GetElementSpaceSize()); DeviceMem c_m_n_device_buf(sizeof(CDataType) * c_m_n_device_result.mDesc.GetElementSpaceSize());
DeviceMem c_m_n_device_ref_buf(sizeof(CDataType) *
c_m_n_device_ref_result.mDesc.GetElementSpaceSize());
a_m_k_device_buf.ToDevice(a_m_k.mData.data()); a_m_k_device_buf.ToDevice(a_m_k.mData.data());
b_k_n_device_buf.ToDevice(b_k_n.mData.data()); b_k_n_device_buf.ToDevice(b_k_n.mData.data());
...@@ -325,14 +328,18 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config) ...@@ -325,14 +328,18 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
<< gemm.GetTypeString() << std::endl; << gemm.GetTypeString() << std::endl;
bool pass = true;
if(config.do_verification) if(config.do_verification)
{ {
// CPU verification
auto ref_gemm = ReferenceGemmInstance{}; auto ref_gemm = ReferenceGemmInstance{};
auto ref_invoker = ref_gemm.MakeInvoker(); auto ref_invoker = ref_gemm.MakeInvoker();
auto ref_argument = ref_gemm.MakeArgument( auto ref_argument = ref_gemm.MakeArgument(
a_m_k, b_k_n, c_m_n_host_result, a_element_op, b_element_op, c_element_op); a_m_k, b_k_n, c_m_n_host_result, a_element_op, b_element_op, c_element_op);
std::cout << "Running verification on CPU." << std::endl;
ref_invoker.Run(ref_argument); ref_invoker.Run(ref_argument);
#ifdef BUILD_INT4_EXAMPLE #ifdef BUILD_INT4_EXAMPLE
...@@ -346,15 +353,42 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config) ...@@ -346,15 +353,42 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
#else #else
c_m_n_device_buf.FromDevice(c_m_n_device_result.mData.data()); c_m_n_device_buf.FromDevice(c_m_n_device_result.mData.data());
return ck::utils::check_err(c_m_n_device_result, pass &= !ck::utils::check_err(c_m_n_device_result,
c_m_n_host_result, c_m_n_host_result,
"Error: Incorrect results!", "Error: Incorrect results!",
get_rtol<CDataType>(), get_rtol<CDataType>(),
get_atol<CDataType>()); get_atol<CDataType>());
#endif #endif
// GPU verification
auto ref_gemm_gpu = ReferenceGemmInstanceGPU{};
auto ref_invoker_gpu = ref_gemm_gpu.MakeInvoker();
auto ref_argument_gpu = ref_gemm_gpu.MakeArgument(
static_cast<ADataType*>(a_m_k_device_buf.GetDeviceBuffer()),
static_cast<BDataType*>(b_k_n_device_buf.GetDeviceBuffer()),
static_cast<CDataType*>(c_m_n_device_ref_buf.GetDeviceBuffer()),
M,
N,
K,
a_element_op,
b_element_op,
c_element_op);
std::cout << "Running verification on GPU." << std::endl;
ref_invoker_gpu.Run(ref_argument_gpu, StreamConfig{});
c_m_n_device_ref_buf.FromDevice(c_m_n_device_ref_result.mData.data());
c_m_n_device_buf.FromDevice(c_m_n_device_result.mData.data());
pass &= !ck::utils::check_err(c_m_n_device_result,
c_m_n_device_ref_result,
"Error: Incorrect results!",
get_rtol<CDataType>(),
get_atol<CDataType>());
} }
return true; return !pass;
} }
bool run_gemm_example(int argc, char* argv[]) bool run_gemm_example(int argc, char* argv[])
......
example/01_gemm/run_gemm_example_streamk_v2.inc
View file @ 63b152d6
...@@ -117,9 +117,9 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config) ...@@ -117,9 +117,9 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
auto f_get_default_stride = auto f_get_default_stride =
[](std::size_t row, std::size_t col, ck::index_t stride, auto layout) { [](std::size_t row, std::size_t col, ck::index_t stride, auto layout) {
if(stride == -1) if(stride == 0)
{ {
// give a chance if stride is -1, return a default packed stride // give a chance if stride is 0, return a default packed stride
if constexpr(std::is_same_v<decltype(layout), ck::tensor_layout::gemm::RowMajor>) if constexpr(std::is_same_v<decltype(layout), ck::tensor_layout::gemm::RowMajor>)
{ {
return static_cast<std::size_t>(col); return static_cast<std::size_t>(col);
......
example/44_elementwise_permute/CMakeLists.txt
View file @ 63b152d6
...@@ -5,3 +5,4 @@ add_example_executable(example_elementwise_permute_4D_fp32_col elementwise_permu ...@@ -5,3 +5,4 @@ add_example_executable(example_elementwise_permute_4D_fp32_col elementwise_permu
add_example_executable(example_elementwise_permute_4D_fp16_col elementwise_permute_4D_fp16_col.cpp) add_example_executable(example_elementwise_permute_4D_fp16_col elementwise_permute_4D_fp16_col.cpp)
add_example_executable(example_elementwise_binary_4D_fp16 elementwise_binary_4D_fp16.cpp) add_example_executable(example_elementwise_binary_4D_fp16 elementwise_binary_4D_fp16.cpp)
add_example_executable(example_elementwise_trinary_4D_fp16 elementwise_trinary_4D_fp16.cpp) add_example_executable(example_elementwise_trinary_4D_fp16 elementwise_trinary_4D_fp16.cpp)
add_example_executable(elementwise_scale_permute_amax_2D_fp16_fp8 elementwise_scale_permute_amax_2D_fp16_fp8.cpp)
example/44_elementwise_permute/elementwise_scale_permute_amax_2D_fp16_fp8.cpp 0 → 100644
View file @ 63b152d6
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_elementwise_dynamic_vector_dims_impl.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_reduce_multiblock.hpp"
#include "ck/tensor_operation/gpu/device/reduction_operator_mapping.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_elementwise.hpp"
#include "ck/library/utility/algorithm.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/utility/reduction_enums.hpp"
using F16 = ck::half_t;
using F32 = float;
using F8 = ck::f8_t;
using InputDataType = F16;
using ScaleDataType = F32;
using OutputDataType = F8;
static constexpr ck::index_t NumDim = 2;
constexpr ck::ReduceTensorOp ReduceOpId = ck::ReduceTensorOp::MAX;
constexpr bool PropagateNan = true;
constexpr bool OutputIndex = false;
using ReduceOperation = typename ck::reduce_binary_operator<ReduceOpId>::opType;
struct ScalePassThrough
{
ScalePassThrough(const float alpha = 1.f) : alpha_(alpha) {}
__host__ __device__ constexpr void
operator()(OutputDataType& y0, OutputDataType& y1, const InputDataType& x0) const
{
y0 = ck::type_convert<OutputDataType>(ck::type_convert<ScaleDataType>(x0) * alpha_);
y1 = y0;
}
const ScaleDataType alpha_;
};
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using UnaryAbs = ck::tensor_operation::element_wise::UnaryAbs;
using DeviceElementwisePermuteInstance = ck::tensor_operation::device::DeviceElementwiseImpl<
ck::Tuple<InputDataType>, // InDataTypeTuple
ck::Tuple<OutputDataType, OutputDataType>, // OutDataTypeTuple
ScalePassThrough, // Elementwise
NumDim, // NumDim
256, // BlockSize
128, // M0PerBlock
128, // M1PerBlock
8, // M0PerThread
8, // M1PerThread
ck::Sequence<1, 0>, // ThreadClusterArrangeOrder
ck::Sequence<8>, // InScalarPerVectorSeq
ck::Sequence<8, 1>>; // OutScalarPerVectorSeq
using DeviceReduceInstance =
ck::tensor_operation::device::DeviceReduceMultiBlock<OutputDataType,
OutputDataType,
OutputDataType,
NumDim,
NumDim,
ReduceOperation,
UnaryAbs,
PassThrough,
ck::InMemoryDataOperationEnum::Set,
PropagateNan,
OutputIndex,
false, // HaveIndexInputIfOutputIndex
1024, // BlockSize
1, // MThreadClusterSize
1024, // KThreadClusterSize
1, // MThreadSliceSize
16, // KThreadSliceSize
1, // InSrcVectorDim
16, // InSrceVectorSize
1>; // OutDstVectorSize
void reference_scale_permute_amax(Tensor<InputDataType>& input,
Tensor<OutputDataType>& host_output_scaled_casted_transposed,
Tensor<OutputDataType>& host_output_scaled_casted,
Tensor<OutputDataType>& host_output_amax,
const float scale)
{
ScalePassThrough out_element_op(scale);
const ck::index_t M = input.GetLengths()[0];
const ck::index_t K = input.GetLengths()[1];
for(ck::index_t m = 0; m < M; m++)
{
for(ck::index_t k = 0; k < K; k++)
{
OutputDataType y0, y1;
out_element_op(y0, y1, input(m, k));
host_output_scaled_casted(m, k) = y0;
host_output_scaled_casted_transposed(m, k) = y1;
const OutputDataType y_fabs =
ck::type_convert<OutputDataType>(ck::math::abs(ck::type_convert<float>(y0)));
host_output_amax(0) = ck::math::max(y_fabs, host_output_amax(0));
}
}
}
int main(int argc, char* argv[])
{
bool do_verification = true;
bool time_kernel = true;
const float scale = 2.f;
ck::index_t M = 1024;
ck::index_t K = 1024;
if(argc == 3)
{
M = std::stoi(argv[1]);
K = std::stoi(argv[2]);
}
std::array<ck::index_t, 2> dims = {M, K};
std::array<ck::index_t, 2> in_strides = {K, 1};
std::array<ck::index_t, 2> out_strides = {1, M};
Tensor<InputDataType> input(dims, in_strides);
Tensor<OutputDataType> output_scaled_casted_transposed(dims, out_strides);
Tensor<OutputDataType> output_scaled_casted(dims, in_strides);
Tensor<OutputDataType> output_amax({1});
input.GenerateTensorValue(GeneratorTensor_3<InputDataType>{0.0, 1.0});
DeviceMem input_dev_buf(sizeof(InputDataType) * input.mDesc.GetElementSpaceSize());
DeviceMem output_scaled_casted_transposed_dev_buf(
sizeof(OutputDataType) * output_scaled_casted_transposed.mDesc.GetElementSpaceSize());
DeviceMem output_scaled_casted_dev_buf(sizeof(OutputDataType) *
output_scaled_casted.mDesc.GetElementSpaceSize());
DeviceMem output_amax_dev_buf(sizeof(OutputDataType) * output_amax.mDesc.GetElementSpaceSize());
input_dev_buf.ToDevice(input.mData.data());
std::array<const void*, 1> inputs = {input_dev_buf.GetDeviceBuffer()};
std::array<void*, 2> outputs = {output_scaled_casted_transposed_dev_buf.GetDeviceBuffer(),
output_scaled_casted_dev_buf.GetDeviceBuffer()};
std::cout << "Input: " << input.mDesc << std::endl;
std::cout << "Scale: " << scale << std::endl;
std::cout << "Output scaled casted transposed: " << output_scaled_casted_transposed.mDesc
<< std::endl;
std::cout << "Output scaled casted: " << output_scaled_casted.mDesc << std::endl;
std::cout << "Output amax: " << output_amax.mDesc << std::endl;
auto launch_transpose_scale = [&]() {
auto transposeScale = DeviceElementwisePermuteInstance{};
auto argument = transposeScale.MakeArgumentPointer(dims,
{in_strides},
{out_strides, in_strides},
inputs,
outputs,
ScalePassThrough{scale});
if(!transposeScale.IsSupportedArgument(argument.get()))
{
throw std::runtime_error(
"The runtime parameters seems not supported by the device instance, exiting!");
};
auto transposeScale_invoker_ptr = transposeScale.MakeInvokerPointer();
return transposeScale_invoker_ptr->Run(argument.get(), StreamConfig{nullptr, time_kernel});
};
auto launch_reduce = [&]() {
auto reduce = DeviceReduceInstance{};
auto reduce_argument_ptr =
reduce.MakeArgumentPointer(dims,
in_strides,
{1}, // Output Lengths
{1}, // Output Strides
{0, 1}, // Reduce Dims
static_cast<double>(1.f),
static_cast<double>(0.f),
output_scaled_casted_dev_buf.GetDeviceBuffer(),
nullptr,
output_amax_dev_buf.GetDeviceBuffer(),
nullptr,
UnaryAbs{},
PassThrough{});
if(!reduce.IsSupportedArgument(reduce_argument_ptr.get()))
{
throw std::runtime_error(
"The runtime parameters seems not supported by the device instance, exiting!");
};
auto invoker_ptr = reduce.MakeInvokerPointer();
return invoker_ptr->Run(reduce_argument_ptr.get(), StreamConfig{nullptr, time_kernel});
};
float ave_time = launch_transpose_scale();
ave_time += launch_reduce();
std::cout << "Perf: " << ave_time << " ms" << std::endl;
bool pass = true;
if(do_verification)
{
Tensor<OutputDataType> host_output_scaled_casted_transposed(dims, out_strides);
Tensor<OutputDataType> host_output_scaled_casted(dims, in_strides);
Tensor<OutputDataType> host_output_amax({1});
reference_scale_permute_amax(input,
host_output_scaled_casted_transposed,
host_output_scaled_casted,
host_output_amax,
scale);
output_scaled_casted_transposed_dev_buf.FromDevice(
output_scaled_casted_transposed.mData.data());
output_scaled_casted_dev_buf.FromDevice(output_scaled_casted.mData.data());
output_amax_dev_buf.FromDevice(output_amax.mData.data());
pass &= ck::utils::check_err(output_scaled_casted_transposed.mData,
host_output_scaled_casted_transposed.mData,
"Error: Incorrect results scaled transposed",
1e-3,
1e-3);
pass &= ck::utils::check_err(output_scaled_casted.mData,
host_output_scaled_casted.mData,
"Error: Incorrect results scaled",
1e-3,
1e-3);
pass &= ck::utils::check_err(
output_amax.mData, host_output_amax.mData, "Error: Incorrect results amax", 1e-3, 1e-3);
}
return pass ? 0 : 1;
}
example/66_complex_contraction_bilinear/CMakeLists.txt 0 → 100755
View file @ 63b152d6
add_example_executable(example_complex_contraction_bilinear_xdl_fp32 complex_contraction_bilinear_xdl_fp32.cpp)
add_example_executable(example_complex_contraction_bilinear_xdl_fp64 complex_contraction_bilinear_xdl_fp64.cpp)
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