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#ifndef EIGEN_TEST_CUDA_COMMON_H
#define EIGEN_TEST_CUDA_COMMON_H
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_runtime_api.h>
#include <iostream>
#ifndef __CUDACC__
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_cuda_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_cuda(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); cudaMalloc((void**)(&d_in), in_bytes); cudaMalloc((void**)(&d_out), out_bytes); cudaMemcpy(d_in, in.data(), in_bytes, cudaMemcpyHostToDevice); cudaMemcpy(d_out, out.data(), out_bytes, cudaMemcpyHostToDevice); // 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) );
cudaThreadSynchronize(); run_on_cuda_meta_kernel<<<Grids,Blocks>>>(ker, n, d_in, d_out); cudaThreadSynchronize(); // check inputs have not been modified
cudaMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, cudaMemcpyDeviceToHost); cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost); cudaFree(d_in); cudaFree(d_out); }
template<typename Kernel, typename Input, typename Output> void run_and_compare_to_cuda(const Kernel& ker, int n, const Input& in, Output& out) { Input in_ref, in_cuda; Output out_ref, out_cuda; #ifndef __CUDA_ARCH__
in_ref = in_cuda = in; out_ref = out_cuda = out; #endif
run_on_cpu (ker, n, in_ref, out_ref); run_on_cuda(ker, n, in_cuda, out_cuda); #ifndef __CUDA_ARCH__
VERIFY_IS_APPROX(in_ref, in_cuda); VERIFY_IS_APPROX(out_ref, out_cuda); #endif
}
void ei_test_init_cuda() { int device = 0; cudaDeviceProp deviceProp; cudaGetDeviceProperties(&deviceProp, device); std::cout << "CUDA 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_CUDA_COMMON_H
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