mirror of
https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Clang-format tests, examples, libraries, benchmarks, etc.
This commit is contained in:
Antonio Sánchez
committed by
Rasmus Munk Larsen
Rasmus Munk Larsen
parent
3252ecc7a4
commit
46e9cdb7fe
@@ -2,12 +2,12 @@
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#define EIGEN_TEST_GPU_COMMON_H
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#ifdef EIGEN_USE_HIP
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#include <hip/hip_runtime.h>
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#include <hip/hip_runtime_api.h>
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#include <hip/hip_runtime.h>
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#include <hip/hip_runtime_api.h>
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#else
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#include <cuda.h>
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#include <cuda_runtime.h>
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#include <cuda_runtime_api.h>
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#include <cuda.h>
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#include <cuda_runtime.h>
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#include <cuda_runtime_api.h>
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#endif
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#include <iostream>
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@@ -16,54 +16,46 @@
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dim3 threadIdx, blockDim, blockIdx;
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#endif
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template<typename Kernel, typename Input, typename Output>
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void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out)
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{
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for(int i=0; i<n; i++)
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ker(i, in.data(), out.data());
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template <typename Kernel, typename Input, typename Output>
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void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out) {
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for (int i = 0; i < n; i++) ker(i, in.data(), out.data());
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}
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template<typename Kernel, typename Input, typename Output>
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__global__
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EIGEN_HIP_LAUNCH_BOUNDS_1024
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void run_on_gpu_meta_kernel(const Kernel ker, int n, const Input* in, Output* out)
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{
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int i = threadIdx.x + blockIdx.x*blockDim.x;
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if(i<n) {
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template <typename Kernel, typename Input, typename Output>
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__global__ EIGEN_HIP_LAUNCH_BOUNDS_1024 void run_on_gpu_meta_kernel(const Kernel ker, int n, const Input* in,
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Output* out) {
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int i = threadIdx.x + blockIdx.x * blockDim.x;
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if (i < n) {
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ker(i, in, out);
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}
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}
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template<typename Kernel, typename Input, typename Output>
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void run_on_gpu(const Kernel& ker, int n, const Input& in, Output& out)
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{
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typename Input::Scalar* d_in;
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template <typename Kernel, typename Input, typename Output>
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void run_on_gpu(const Kernel& ker, int n, const Input& in, Output& out) {
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typename Input::Scalar* d_in;
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typename Output::Scalar* d_out;
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std::ptrdiff_t in_bytes = in.size() * sizeof(typename Input::Scalar);
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std::ptrdiff_t in_bytes = in.size() * sizeof(typename Input::Scalar);
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std::ptrdiff_t out_bytes = out.size() * sizeof(typename Output::Scalar);
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gpuMalloc((void**)(&d_in), in_bytes);
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gpuMalloc((void**)(&d_in), in_bytes);
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gpuMalloc((void**)(&d_out), out_bytes);
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gpuMemcpy(d_in, in.data(), in_bytes, gpuMemcpyHostToDevice);
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gpuMemcpy(d_in, in.data(), in_bytes, gpuMemcpyHostToDevice);
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gpuMemcpy(d_out, out.data(), out_bytes, gpuMemcpyHostToDevice);
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// Simple and non-optimal 1D mapping assuming n is not too large
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// That's only for unit testing!
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dim3 Blocks(128);
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dim3 Grids( (n+int(Blocks.x)-1)/int(Blocks.x) );
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dim3 Grids((n + int(Blocks.x) - 1) / int(Blocks.x));
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gpuDeviceSynchronize();
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#ifdef EIGEN_USE_HIP
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hipLaunchKernelGGL(HIP_KERNEL_NAME(run_on_gpu_meta_kernel<Kernel,
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typename std::decay<decltype(*d_in)>::type,
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typename std::decay<decltype(*d_out)>::type>),
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dim3(Grids), dim3(Blocks), 0, 0, ker, n, d_in, d_out);
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hipLaunchKernelGGL(HIP_KERNEL_NAME(run_on_gpu_meta_kernel<Kernel, typename std::decay<decltype(*d_in)>::type,
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typename std::decay<decltype(*d_out)>::type>),
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dim3(Grids), dim3(Blocks), 0, 0, ker, n, d_in, d_out);
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#else
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run_on_gpu_meta_kernel<<<Grids,Blocks>>>(ker, n, d_in, d_out);
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run_on_gpu_meta_kernel<<<Grids, Blocks> > >(ker, n, d_in, d_out);
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#endif
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// Pre-launch errors.
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gpuError_t err = gpuGetLastError();
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@@ -71,90 +63,83 @@ void run_on_gpu(const Kernel& ker, int n, const Input& in, Output& out)
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printf("%s: %s\n", gpuGetErrorName(err), gpuGetErrorString(err));
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gpu_assert(false);
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}
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// Kernel execution errors.
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err = gpuDeviceSynchronize();
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if (err != gpuSuccess) {
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printf("%s: %s\n", gpuGetErrorName(err), gpuGetErrorString(err));
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gpu_assert(false);
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}
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// check inputs have not been modified
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gpuMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, gpuMemcpyDeviceToHost);
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gpuMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, gpuMemcpyDeviceToHost);
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gpuMemcpy(out.data(), d_out, out_bytes, gpuMemcpyDeviceToHost);
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gpuFree(d_in);
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gpuFree(d_out);
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}
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template<typename Kernel, typename Input, typename Output>
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void run_and_compare_to_gpu(const Kernel& ker, int n, const Input& in, Output& out)
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{
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Input in_ref, in_gpu;
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template <typename Kernel, typename Input, typename Output>
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void run_and_compare_to_gpu(const Kernel& ker, int n, const Input& in, Output& out) {
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Input in_ref, in_gpu;
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Output out_ref, out_gpu;
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#if !defined(EIGEN_GPU_COMPILE_PHASE)
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#if !defined(EIGEN_GPU_COMPILE_PHASE)
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in_ref = in_gpu = in;
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out_ref = out_gpu = out;
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#else
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#else
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EIGEN_UNUSED_VARIABLE(in);
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EIGEN_UNUSED_VARIABLE(out);
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#endif
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run_on_cpu (ker, n, in_ref, out_ref);
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#endif
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run_on_cpu(ker, n, in_ref, out_ref);
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run_on_gpu(ker, n, in_gpu, out_gpu);
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#if !defined(EIGEN_GPU_COMPILE_PHASE)
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#if !defined(EIGEN_GPU_COMPILE_PHASE)
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VERIFY_IS_APPROX(in_ref, in_gpu);
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VERIFY_IS_APPROX(out_ref, out_gpu);
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#endif
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#endif
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}
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struct compile_time_device_info {
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EIGEN_DEVICE_FUNC
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void operator()(int i, const int* /*in*/, int* info) const
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{
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EIGEN_DEVICE_FUNC void operator()(int i, const int* /*in*/, int* info) const {
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if (i == 0) {
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EIGEN_UNUSED_VARIABLE(info)
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#if defined(__CUDA_ARCH__)
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info[0] = int(__CUDA_ARCH__ +0);
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#endif
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#if defined(EIGEN_HIP_DEVICE_COMPILE)
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info[1] = int(EIGEN_HIP_DEVICE_COMPILE +0);
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#endif
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#if defined(__CUDA_ARCH__)
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info[0] = int(__CUDA_ARCH__ + 0);
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#endif
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#if defined(EIGEN_HIP_DEVICE_COMPILE)
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info[1] = int(EIGEN_HIP_DEVICE_COMPILE + 0);
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#endif
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}
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}
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};
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void ei_test_init_gpu()
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{
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void ei_test_init_gpu() {
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int device = 0;
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gpuDeviceProp_t deviceProp;
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gpuGetDeviceProperties(&deviceProp, device);
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ArrayXi dummy(1), info(10);
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info = -1;
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run_on_gpu(compile_time_device_info(),10,dummy,info);
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run_on_gpu(compile_time_device_info(), 10, dummy, info);
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std::cout << "GPU compile-time info:\n";
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#ifdef EIGEN_CUDACC
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#ifdef EIGEN_CUDACC
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std::cout << " EIGEN_CUDACC: " << int(EIGEN_CUDACC) << "\n";
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#endif
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#ifdef EIGEN_CUDA_SDK_VER
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#endif
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#ifdef EIGEN_CUDA_SDK_VER
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std::cout << " EIGEN_CUDA_SDK_VER: " << int(EIGEN_CUDA_SDK_VER) << "\n";
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#endif
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#endif
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#if EIGEN_COMP_NVCC
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#if EIGEN_COMP_NVCC
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std::cout << " EIGEN_COMP_NVCC: " << int(EIGEN_COMP_NVCC) << "\n";
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#endif
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#ifdef EIGEN_HIPCC
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std::cout << " EIGEN_HIPCC: " << int(EIGEN_HIPCC) << "\n";
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#endif
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#endif
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std::cout << " EIGEN_CUDA_ARCH: " << info[0] << "\n";
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#ifdef EIGEN_HIPCC
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std::cout << " EIGEN_HIPCC: " << int(EIGEN_HIPCC) << "\n";
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#endif
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std::cout << " EIGEN_CUDA_ARCH: " << info[0] << "\n";
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std::cout << " EIGEN_HIP_DEVICE_COMPILE: " << info[1] << "\n";
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std::cout << "GPU device info:\n";
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@@ -170,4 +155,4 @@ void ei_test_init_gpu()
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std::cout << " computeMode: " << deviceProp.computeMode << "\n";
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}
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#endif // EIGEN_TEST_GPU_COMMON_H
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#endif // EIGEN_TEST_GPU_COMMON_H
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