cart-elc

Source code for CART-ELC
git clone git://git.laack.co/cart-elc.git
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cxx11_tensor_scan_gpu.cu (2576B)


      1 // This file is part of Eigen, a lightweight C++ template library
      2 // for linear algebra.
      3 //
      4 // Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
      5 //
      6 // This Source Code Form is subject to the terms of the Mozilla
      7 // Public License v. 2.0. If a copy of the MPL was not distributed
      8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
      9 
     10 #define EIGEN_TEST_NO_LONGDOUBLE
     11 #define EIGEN_TEST_NO_COMPLEX
     12 
     13 #define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
     14 #define EIGEN_USE_GPU
     15 
     16 #include "main.h"
     17 #include <unsupported/Eigen/CXX11/Tensor>
     18 
     19 #include <Eigen/CXX11/src/Tensor/TensorGpuHipCudaDefines.h>
     20 
     21 using Eigen::Tensor;
     22 typedef Tensor<float, 1>::DimensionPair DimPair;
     23 
     24 template<int DataLayout>
     25 void test_gpu_cumsum(int m_size, int k_size, int n_size)
     26 {
     27   std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
     28   Tensor<float, 3, DataLayout> t_input(m_size, k_size, n_size);
     29   Tensor<float, 3, DataLayout> t_result(m_size, k_size, n_size);
     30   Tensor<float, 3, DataLayout> t_result_gpu(m_size, k_size, n_size);
     31 
     32   t_input.setRandom();
     33 
     34   std::size_t t_input_bytes = t_input.size()  * sizeof(float);
     35   std::size_t t_result_bytes = t_result.size() * sizeof(float);
     36 
     37   float* d_t_input;
     38   float* d_t_result;
     39 
     40   gpuMalloc((void**)(&d_t_input), t_input_bytes);
     41   gpuMalloc((void**)(&d_t_result), t_result_bytes);
     42 
     43   gpuMemcpy(d_t_input, t_input.data(), t_input_bytes, gpuMemcpyHostToDevice);
     44 
     45   Eigen::GpuStreamDevice stream;
     46   Eigen::GpuDevice gpu_device(&stream);
     47 
     48   Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
     49       gpu_t_input(d_t_input, Eigen::array<int, 3>(m_size, k_size, n_size));
     50   Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
     51       gpu_t_result(d_t_result, Eigen::array<int, 3>(m_size, k_size, n_size));
     52 
     53   gpu_t_result.device(gpu_device) = gpu_t_input.cumsum(1);
     54   t_result = t_input.cumsum(1);
     55 
     56   gpuMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, gpuMemcpyDeviceToHost);
     57   for (DenseIndex i = 0; i < t_result.size(); i++) {
     58     if (fabs(t_result(i) - t_result_gpu(i)) < 1e-4f) {
     59       continue;
     60     }
     61     if (Eigen::internal::isApprox(t_result(i), t_result_gpu(i), 1e-4f)) {
     62       continue;
     63     }
     64     std::cout << "mismatch detected at index " << i << ": " << t_result(i)
     65               << " vs " <<  t_result_gpu(i) << std::endl;
     66     assert(false);
     67   }
     68 
     69   gpuFree((void*)d_t_input);
     70   gpuFree((void*)d_t_result);
     71 }
     72 
     73 
     74 EIGEN_DECLARE_TEST(cxx11_tensor_scan_gpu)
     75 {
     76   CALL_SUBTEST_1(test_gpu_cumsum<ColMajor>(128, 128, 128));
     77   CALL_SUBTEST_2(test_gpu_cumsum<RowMajor>(128, 128, 128));
     78 }