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				| 
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| #ifndef STORMEIGEN_TEST_CUDA_COMMON_H | |
| #define STORMEIGEN_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 // STORMEIGEN_TEST_CUDA_COMMON_H
 |