diff options
author | Luke Iwanski <luke@codeplay.com> | 2016-09-19 12:44:13 +0100 |
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committer | Luke Iwanski <luke@codeplay.com> | 2016-09-19 12:44:13 +0100 |
commit | cb81975714a96ecb2faf33ca242feeee3543b1db (patch) | |
tree | febc8730a60a48572cb293696c170d7cb50a4728 /unsupported/test/cxx11_tensor_sycl_broadcast.cpp | |
parent | 59bacfe5201b54a6303b79bb538671d04f91dbce (diff) |
Partial OpenCL support via SYCL compatible with ComputeCpp CE.
Diffstat (limited to 'unsupported/test/cxx11_tensor_sycl_broadcast.cpp')
-rw-r--r-- | unsupported/test/cxx11_tensor_sycl_broadcast.cpp | 76 |
1 files changed, 76 insertions, 0 deletions
diff --git a/unsupported/test/cxx11_tensor_sycl_broadcast.cpp b/unsupported/test/cxx11_tensor_sycl_broadcast.cpp new file mode 100644 index 000000000..1babbc038 --- /dev/null +++ b/unsupported/test/cxx11_tensor_sycl_broadcast.cpp @@ -0,0 +1,76 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com> +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + + +#define EIGEN_TEST_NO_LONGDOUBLE +#define EIGEN_TEST_NO_COMPLEX +#define EIGEN_TEST_FUNC cxx11_tensor_sycl_broadcast +#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int +#define EIGEN_USE_SYCL + +#include "main.h" +#include <unsupported/Eigen/CXX11/Tensor> + +using Eigen::array; +using Eigen::SyclDevice; +using Eigen::Tensor; +using Eigen::TensorMap; + +// Types used in tests: +using TestTensor = Tensor<float, 3>; +using TestTensorMap = TensorMap<Tensor<float, 3>>; +static void test_sycl_broadcast(){ + + cl::sycl::gpu_selector s; + cl::sycl::queue q(s, [=](cl::sycl::exception_list l) { + for (const auto& e : l) { + try { + std::rethrow_exception(e); + } catch (cl::sycl::exception e) { + std::cout << e.what() << std::endl; + } + } + }); + SyclDevice sycl_device(q); + // BROADCAST test: + array<int, 4> in_range = {{2, 3, 5, 7}}; + array<int, in_range.size()> broadcasts = {{2, 3, 1, 4}}; + array<int, in_range.size()> out_range; // = in_range * broadcasts + for (size_t i = 0; i < out_range.size(); ++i) + out_range[i] = in_range[i] * broadcasts[i]; + + Tensor<float, in_range.size()> input(in_range); + Tensor<float, out_range.size()> output(out_range); + + for (int i = 0; i < input.size(); ++i) + input(i) = static_cast<float>(i); + + TensorMap<decltype(input)> gpu_in(input.data(), in_range); + TensorMap<decltype(output)> gpu_out(output.data(), out_range); + gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts); + sycl_device.deallocate(output.data()); + + for (size_t i = 0; i < in_range.size(); ++i) + VERIFY_IS_EQUAL(output.dimension(i), out_range[i]); + + for (int i = 0; i < 4; ++i) { + for (int j = 0; j < 9; ++j) { + for (int k = 0; k < 5; ++k) { + for (int l = 0; l < 28; ++l) { + VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), output(i,j,k,l)); + } + } + } + } + printf("Broadcast Test Passed\n"); +} + +void test_cxx11_tensor_sycl_broadcast() { + CALL_SUBTEST(test_sycl_broadcast()); +} |