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Diffstat (limited to 'test/gpu_common.h')
| -rw-r--r-- | test/gpu_common.h | 176 |
1 files changed, 176 insertions, 0 deletions
diff --git a/test/gpu_common.h b/test/gpu_common.h new file mode 100644 index 000000000..c37eaa13f --- /dev/null +++ b/test/gpu_common.h @@ -0,0 +1,176 @@ +#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__ +EIGEN_HIP_LAUNCH_BOUNDS_1024 +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 + // Pre-launch errors. + gpuError_t err = gpuGetLastError(); + if (err != gpuSuccess) { + printf("%s: %s\n", gpuGetErrorName(err), gpuGetErrorString(err)); + gpu_assert(false); + } + + // Kernel execution errors. + err = gpuDeviceSynchronize(); + if (err != gpuSuccess) { + printf("%s: %s\n", gpuGetErrorName(err), gpuGetErrorString(err)); + gpu_assert(false); + } + + + // 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(EIGEN_GPU_COMPILE_PHASE) + 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(EIGEN_GPU_COMPILE_PHASE) + 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 (i == 0) { + EIGEN_UNUSED_VARIABLE(info) + #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 |