2016-09-19 19:44:13 +08:00
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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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2016-09-19 21:09:25 +08:00
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// Copyright (C) 2016
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// Mehdi Goli Codeplay Software Ltd.
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// Ralph Potter Codeplay Software Ltd.
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// Luke Iwanski Codeplay Software Ltd.
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// Contact: <eigen@codeplay.com>
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2016-09-19 19:44:13 +08:00
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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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2016-10-06 05:24:24 +08:00
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#define EIGEN_TEST_FUNC cxx11_tensor_device_sycl
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2016-09-19 19:44:13 +08:00
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#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
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#define EIGEN_USE_SYCL
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#include "main.h"
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#include <unsupported/Eigen/CXX11/Tensor>
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2016-11-11 02:45:12 +08:00
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#include<stdint.h>
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2016-09-19 19:44:13 +08:00
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2016-11-18 12:27:54 +08:00
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void test_device_memory(const Eigen::SyclDevice &sycl_device) {
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std::cout << "Running on: "
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<< sycl_device.m_queue.get_device(). template get_info<cl::sycl::info::device::name>()
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<< std::endl;
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2016-11-11 02:45:12 +08:00
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int sizeDim1 = 100;
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array<int, 1> tensorRange = {{sizeDim1}};
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Tensor<int, 1> in(tensorRange);
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Tensor<int, 1> in1(tensorRange);
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2016-11-11 03:16:31 +08:00
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memset(in1.data(), 1,in1.size()*sizeof(int));
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2016-11-18 12:27:54 +08:00
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int* gpu_in_data = static_cast<int*>(sycl_device.allocate(in.size()*sizeof(int)));
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sycl_device.memset(gpu_in_data, 1, in.size()*sizeof(int) );
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2016-11-11 03:16:31 +08:00
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sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(int) );
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2016-11-18 12:27:54 +08:00
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for (int i=0; i<in.size(); i++) {
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2016-11-11 02:45:12 +08:00
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VERIFY_IS_APPROX(in(i), in1(i));
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2016-11-18 12:27:54 +08:00
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}
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2016-11-11 02:45:12 +08:00
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sycl_device.deallocate(gpu_in_data);
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2016-09-19 19:44:13 +08:00
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}
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2016-11-18 12:27:54 +08:00
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void test_device_exceptions(const Eigen::SyclDevice &sycl_device) {
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2016-11-18 13:51:48 +08:00
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VERIFY(sycl_device.ok());
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2016-11-18 12:27:54 +08:00
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array<int, 1> tensorDims = {{100}};
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int* gpu_data = static_cast<int*>(sycl_device.allocate(100*sizeof(int)));
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TensorMap<Tensor<int, 1>> in(gpu_data, tensorDims);
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TensorMap<Tensor<int, 1>> out(gpu_data, tensorDims);
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2016-11-18 13:51:48 +08:00
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out.device(sycl_device) = in / in.constant(0);
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VERIFY(!sycl_device.ok());
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2016-11-18 12:27:54 +08:00
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sycl_device.deallocate(gpu_data);
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}
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2016-10-06 05:24:24 +08:00
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void test_cxx11_tensor_device_sycl() {
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2016-11-09 01:08:02 +08:00
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cl::sycl::gpu_selector s;
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Eigen::SyclDevice sycl_device(s);
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2016-11-18 12:27:54 +08:00
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CALL_SUBTEST(test_device_memory(sycl_device));
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// This deadlocks
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2016-11-18 13:51:48 +08:00
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//CALL_SUBTEST(test_device_exceptions(sycl_device));
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2016-09-19 19:44:13 +08:00
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}
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