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https://gitlab.com/libeigen/eigen.git
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c64fe9ea1f
Compiling the eigen unittests with hip-clang (HIP with clang as the underlying compiler instead of hcc or nvcc), results in compile errors. The changes in this commit fix those compile errors. The main change is to convert a few instances of "__device__" to "EIGEN_DEVICE_FUNC"
158 lines
4.8 KiB
C++
158 lines
4.8 KiB
C++
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#ifndef EIGEN_TEST_GPU_COMMON_H
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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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#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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#endif
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#include <iostream>
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#define EIGEN_USE_GPU
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#include <unsupported/Eigen/CXX11/src/Tensor/TensorGpuHipCudaDefines.h>
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#if !defined(__CUDACC__) && !defined(__HIPCC__)
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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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}
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template<typename Kernel, typename Input, typename Output>
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__global__
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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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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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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 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_out), out_bytes);
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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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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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#else
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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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gpuDeviceSynchronize();
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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(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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Output out_ref, out_gpu;
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#if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__)
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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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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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run_on_gpu(ker, n, in_gpu, out_gpu);
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#if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__)
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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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}
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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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#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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void ei_test_init_gpu()
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{
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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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std::cout << "GPU compile-time info:\n";
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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_CUDACC_VER
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std::cout << " EIGEN_CUDACC_VER: " << int(EIGEN_CUDACC_VER) << "\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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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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std::cout << " name: " << deviceProp.name << "\n";
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std::cout << " capability: " << deviceProp.major << "." << deviceProp.minor << "\n";
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std::cout << " multiProcessorCount: " << deviceProp.multiProcessorCount << "\n";
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std::cout << " maxThreadsPerMultiProcessor: " << deviceProp.maxThreadsPerMultiProcessor << "\n";
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std::cout << " warpSize: " << deviceProp.warpSize << "\n";
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std::cout << " regsPerBlock: " << deviceProp.regsPerBlock << "\n";
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std::cout << " concurrentKernels: " << deviceProp.concurrentKernels << "\n";
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std::cout << " clockRate: " << deviceProp.clockRate << "\n";
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std::cout << " canMapHostMemory: " << deviceProp.canMapHostMemory << "\n";
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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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