| #ifndef EIGEN_TEST_GPU_COMMON_H | |
| #define EIGEN_TEST_GPU_COMMON_H | |
| #ifdef EIGEN_USE_HIP | |
| #include <hip/hip_runtime.h> | |
| #include <hip/hip_runtime_api.h> | |
| #else | |
| #include <cuda.h> | |
| #include <cuda_runtime.h> | |
| #include <cuda_runtime_api.h> | |
| #endif | |
| #include <iostream> | |
| #define EIGEN_USE_GPU | |
| #include <unsupported/Eigen/CXX11/src/Tensor/TensorGpuHipCudaDefines.h> | |
| #if !defined(__CUDACC__) && !defined(__HIPCC__) | |
| dim3 threadIdx, blockDim, blockIdx; | |
| #endif | |
| template<typename Kernel, typename Input, typename Output> | |
| void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out) | |
| { | |
| for(int i=0; i<n; i++) | |
| ker(i, in.data(), out.data()); | |
| } | |
| template<typename Kernel, typename Input, typename Output> | |
| __global__ | |
| void run_on_gpu_meta_kernel(const Kernel ker, int n, const Input* in, Output* out) | |
| { | |
| int i = threadIdx.x + blockIdx.x*blockDim.x; | |
| if(i<n) { | |
| ker(i, in, out); | |
| } | |
| } | |
| template<typename Kernel, typename Input, typename Output> | |
| void run_on_gpu(const Kernel& ker, int n, const Input& in, Output& out) | |
| { | |
| typename Input::Scalar* d_in; | |
| typename Output::Scalar* d_out; | |
| std::ptrdiff_t in_bytes = in.size() * sizeof(typename Input::Scalar); | |
| std::ptrdiff_t out_bytes = out.size() * sizeof(typename Output::Scalar); | |
| gpuMalloc((void**)(&d_in), in_bytes); | |
| gpuMalloc((void**)(&d_out), out_bytes); | |
| gpuMemcpy(d_in, in.data(), in_bytes, gpuMemcpyHostToDevice); | |
| gpuMemcpy(d_out, out.data(), out_bytes, gpuMemcpyHostToDevice); | |
| // Simple and non-optimal 1D mapping assuming n is not too large | |
| // That's only for unit testing! | |
| dim3 Blocks(128); | |
| dim3 Grids( (n+int(Blocks.x)-1)/int(Blocks.x) ); | |
| gpuDeviceSynchronize(); | |
| #ifdef EIGEN_USE_HIP | |
| hipLaunchKernelGGL(HIP_KERNEL_NAME(run_on_gpu_meta_kernel<Kernel, | |
| typename std::decay<decltype(*d_in)>::type, | |
| typename std::decay<decltype(*d_out)>::type>), | |
| dim3(Grids), dim3(Blocks), 0, 0, ker, n, d_in, d_out); | |
| #else | |
| run_on_gpu_meta_kernel<<<Grids,Blocks>>>(ker, n, d_in, d_out); | |
| #endif | |
| gpuDeviceSynchronize(); | |
| // check inputs have not been modified | |
| gpuMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, gpuMemcpyDeviceToHost); | |
| gpuMemcpy(out.data(), d_out, out_bytes, gpuMemcpyDeviceToHost); | |
| gpuFree(d_in); | |
| gpuFree(d_out); | |
| } | |
| template<typename Kernel, typename Input, typename Output> | |
| void run_and_compare_to_gpu(const Kernel& ker, int n, const Input& in, Output& out) | |
| { | |
| Input in_ref, in_gpu; | |
| Output out_ref, out_gpu; | |
| #if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__) | |
| in_ref = in_gpu = in; | |
| out_ref = out_gpu = out; | |
| #else | |
| EIGEN_UNUSED_VARIABLE(in); | |
| EIGEN_UNUSED_VARIABLE(out); | |
| #endif | |
| run_on_cpu (ker, n, in_ref, out_ref); | |
| run_on_gpu(ker, n, in_gpu, out_gpu); | |
| #if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__) | |
| VERIFY_IS_APPROX(in_ref, in_gpu); | |
| VERIFY_IS_APPROX(out_ref, out_gpu); | |
| #endif | |
| } | |
| struct compile_time_device_info { | |
| EIGEN_DEVICE_FUNC | |
| void operator()(int /*i*/, const int* /*in*/, int* info) const | |
| { | |
| #if defined(__CUDA_ARCH__) | |
| info[0] = int(__CUDA_ARCH__ +0); | |
| #endif | |
| #if defined(EIGEN_HIP_DEVICE_COMPILE) | |
| info[1] = int(EIGEN_HIP_DEVICE_COMPILE +0); | |
| #endif | |
| } | |
| }; | |
| void ei_test_init_gpu() | |
| { | |
| int device = 0; | |
| gpuDeviceProp_t deviceProp; | |
| gpuGetDeviceProperties(&deviceProp, device); | |
| ArrayXi dummy(1), info(10); | |
| info = -1; | |
| run_on_gpu(compile_time_device_info(),10,dummy,info); | |
| std::cout << "GPU compile-time info:\n"; | |
| #ifdef EIGEN_CUDACC | |
| std::cout << " EIGEN_CUDACC: " << int(EIGEN_CUDACC) << "\n"; | |
| #endif | |
| #ifdef EIGEN_CUDA_SDK_VER | |
| std::cout << " EIGEN_CUDA_SDK_VER: " << int(EIGEN_CUDA_SDK_VER) << "\n"; | |
| #endif | |
| #ifdef EIGEN_COMP_NVCC | |
| std::cout << " EIGEN_COMP_NVCC: " << int(EIGEN_COMP_NVCC) << "\n"; | |
| #endif | |
| #ifdef EIGEN_HIPCC | |
| std::cout << " EIGEN_HIPCC: " << int(EIGEN_HIPCC) << "\n"; | |
| #endif | |
| std::cout << " EIGEN_CUDA_ARCH: " << info[0] << "\n"; | |
| std::cout << " EIGEN_HIP_DEVICE_COMPILE: " << info[1] << "\n"; | |
| std::cout << "GPU device info:\n"; | |
| std::cout << " name: " << deviceProp.name << "\n"; | |
| std::cout << " capability: " << deviceProp.major << "." << deviceProp.minor << "\n"; | |
| std::cout << " multiProcessorCount: " << deviceProp.multiProcessorCount << "\n"; | |
| std::cout << " maxThreadsPerMultiProcessor: " << deviceProp.maxThreadsPerMultiProcessor << "\n"; | |
| std::cout << " warpSize: " << deviceProp.warpSize << "\n"; | |
| std::cout << " regsPerBlock: " << deviceProp.regsPerBlock << "\n"; | |
| std::cout << " concurrentKernels: " << deviceProp.concurrentKernels << "\n"; | |
| std::cout << " clockRate: " << deviceProp.clockRate << "\n"; | |
| std::cout << " canMapHostMemory: " << deviceProp.canMapHostMemory << "\n"; | |
| std::cout << " computeMode: " << deviceProp.computeMode << "\n"; | |
| } | |
| #endif // EIGEN_TEST_GPU_COMMON_H |