unsupported/test/cxx11_tensor_device_sycl.cpp

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016
// Mehdi Goli    Codeplay Software Ltd.
// Ralph Potter  Codeplay Software Ltd.
// Luke Iwanski  Codeplay Software Ltd.
// Contact: <eigen@codeplay.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_device_sycl
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
#define EIGEN_USE_SYCL

#include "main.h"
#include <unsupported/Eigen/CXX11/Tensor>
#include<stdint.h>

void test_device_sycl(const Eigen::SyclDevice &sycl_device) {
  std::cout <<"Helo from ComputeCpp: the requested device exists and the device name is : "
    << sycl_device.m_queue.get_device(). template get_info<cl::sycl::info::device::name>() <<std::endl;;
  int sizeDim1 = 100;

  array<int, 1> tensorRange = {{sizeDim1}};
  Tensor<int, 1> in(tensorRange);
  Tensor<int, 1> in1(tensorRange);
  memset(in1.data(), 1,in1.size()*sizeof(int));
  int * gpu_in_data  = static_cast<int*>(sycl_device.allocate(in.size()*sizeof(int)));
  sycl_device.memset(gpu_in_data, 1,in.size()*sizeof(int) );
  sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(int) );
  for (int i=0; i<in.size(); i++)
    VERIFY_IS_APPROX(in(i), in1(i));
  sycl_device.deallocate(gpu_in_data);
}
void test_cxx11_tensor_device_sycl() {
  cl::sycl::gpu_selector s;
  Eigen::SyclDevice sycl_device(s);
  CALL_SUBTEST(test_device_sycl(sycl_device));
}