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78 lines
2.5 KiB
Plaintext
78 lines
2.5 KiB
Plaintext
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#define EIGEN_TEST_NO_LONGDOUBLE
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#define EIGEN_TEST_NO_COMPLEX
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#define EIGEN_TEST_FUNC cxx11_tensor_scan_cuda
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#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
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#define EIGEN_USE_GPU
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#include "main.h"
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#include <unsupported/Eigen/CXX11/Tensor>
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using Eigen::Tensor;
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typedef Tensor<float, 1>::DimensionPair DimPair;
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template<int DataLayout>
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void test_cuda_cumsum(int m_size, int k_size, int n_size)
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{
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std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
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Tensor<float, 3, DataLayout> t_input(m_size, k_size, n_size);
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Tensor<float, 3, DataLayout> t_result(m_size, k_size, n_size);
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Tensor<float, 3, DataLayout> t_result_gpu(m_size, k_size, n_size);
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t_input.setRandom();
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std::size_t t_input_bytes = t_input.size() * sizeof(float);
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std::size_t t_result_bytes = t_result.size() * sizeof(float);
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float* d_t_input;
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float* d_t_result;
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cudaMalloc((void**)(&d_t_input), t_input_bytes);
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cudaMalloc((void**)(&d_t_result), t_result_bytes);
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cudaMemcpy(d_t_input, t_input.data(), t_input_bytes, cudaMemcpyHostToDevice);
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Eigen::CudaStreamDevice stream;
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Eigen::GpuDevice gpu_device(&stream);
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Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
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gpu_t_input(d_t_input, Eigen::array<int, 3>(m_size, k_size, n_size));
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Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
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gpu_t_result(d_t_result, Eigen::array<int, 3>(m_size, k_size, n_size));
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gpu_t_result.device(gpu_device) = gpu_t_input.cumsum(1);
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t_result = t_input.cumsum(1);
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cudaMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, cudaMemcpyDeviceToHost);
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for (size_t i = 0; i < t_result.size(); i++) {
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if (fabs(t_result(i) - t_result_gpu(i)) < 1e-4f) {
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continue;
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}
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if (Eigen::internal::isApprox(t_result(i), t_result_gpu(i), 1e-4f)) {
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continue;
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}
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std::cout << "mismatch detected at index " << i << ": " << t_result(i)
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<< " vs " << t_result_gpu(i) << std::endl;
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assert(false);
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}
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cudaFree((void*)d_t_input);
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cudaFree((void*)d_t_result);
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}
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void test_cxx11_tensor_scan_cuda()
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{
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CALL_SUBTEST_1(test_cuda_cumsum<ColMajor>(128, 128, 128));
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CALL_SUBTEST_2(test_cuda_cumsum<RowMajor>(128, 128, 128));
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}
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