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aad03486d9
This adds interoperability support between Boost.Compute and various other C/C++ libraries (Eigen, OpenCV, OpenGL, Qt and VTK). This eases development for users using external libraries with Boost.Compute.
103 lines
3.6 KiB
C++
103 lines
3.6 KiB
C++
//---------------------------------------------------------------------------//
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// Copyright (c) 2013-2014 Kyle Lutz <kyle.r.lutz@gmail.com>
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//
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// Distributed under the Boost Software License, Version 1.0
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// See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt
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//
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// See http://kylelutz.github.com/compute for more information.
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//---------------------------------------------------------------------------//
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#define BOOST_TEST_MODULE TestInteropEigen
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#include <boost/test/unit_test.hpp>
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#include <boost/compute/system.hpp>
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#include <boost/compute/container/vector.hpp>
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#include <boost/compute/algorithm/transform.hpp>
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#include <boost/compute/interop/eigen.hpp>
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#include "check_macros.hpp"
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#include "context_setup.hpp"
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namespace bcl = boost::compute;
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BOOST_AUTO_TEST_CASE(eigen)
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{
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Eigen::MatrixXf mat(3, 3);
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mat << 1, 2, 3,
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6, 5, 4,
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7, 8, 9;
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// copy matrix to gpu buffer
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bcl::vector<float> vec(9, context);
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bcl::eigen_copy_matrix_to_buffer(mat, vec.begin(), queue);
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CHECK_RANGE_EQUAL(float, 9, vec, (1, 6, 7, 2, 5, 8, 3, 4, 9));
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// transpose matrix and then copy to gpu buffer
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mat = mat.transpose().eval();
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bcl::eigen_copy_matrix_to_buffer(mat, vec.begin(), queue);
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CHECK_RANGE_EQUAL(float, 9, vec, (1, 2, 3, 6, 5, 4, 7, 8, 9));
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// set matrix to zero and copy data back from gpu buffer
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mat.setZero();
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bcl::eigen_copy_buffer_to_matrix(vec.begin(), mat, queue);
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BOOST_CHECK(mat.isZero() == false);
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BOOST_CHECK_EQUAL(mat.sum(), 45);
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}
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BOOST_AUTO_TEST_CASE(eigen_types)
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{
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BOOST_CHECK(std::strcmp(bcl::type_name<Eigen::Vector2i>(), "int2") == 0);
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BOOST_CHECK(std::strcmp(bcl::type_name<Eigen::Vector2f>(), "float2") == 0);
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BOOST_CHECK(std::strcmp(bcl::type_name<Eigen::Vector4f>(), "float4") == 0);
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BOOST_CHECK(std::strcmp(bcl::type_name<Eigen::Vector4d>(), "double4") == 0);
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}
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BOOST_AUTO_TEST_CASE(multiply_matrix4)
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{
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std::vector<Eigen::Vector4f> host_vectors;
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std::vector<Eigen::Matrix4f> host_matrices;
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host_matrices.push_back(Eigen::Matrix4f::Identity());
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host_matrices.push_back(Eigen::Matrix4f::Zero());
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host_matrices.push_back(Eigen::Matrix4f::Ones());
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host_matrices.push_back(Eigen::Matrix4f::Ones() * 2);
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host_vectors.push_back(Eigen::Vector4f(1, 2, 3, 4));
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host_vectors.push_back(Eigen::Vector4f(4, 3, 2, 1));
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host_vectors.push_back(Eigen::Vector4f(1, 2, 3, 4));
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host_vectors.push_back(Eigen::Vector4f(4, 3, 2, 1));
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// returns the result of M*x
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BOOST_COMPUTE_FUNCTION(Eigen::Vector4f, transform4x4, (const Eigen::Matrix4f, const Eigen::Vector4f),
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{
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float4 r;
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r.x = dot(_1.s048c, _2);
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r.y = dot(_1.s159d, _2);
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r.z = dot(_1.s26ae, _2);
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r.w = dot(_1.s37bf, _2);
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return r;
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});
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bcl::vector<Eigen::Vector4f> vectors(4, context);
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bcl::vector<Eigen::Matrix4f> matrices(4, context);
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bcl::vector<Eigen::Vector4f> results(4, context);
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bcl::copy(host_vectors.begin(), host_vectors.end(), vectors.begin(), queue);
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bcl::copy(host_matrices.begin(), host_matrices.end(), matrices.begin(), queue);
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bcl::transform(
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matrices.begin(), matrices.end(), vectors.begin(), results.begin(), transform4x4, queue
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);
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std::vector<Eigen::Vector4f> host_results(4);
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bcl::copy(results.begin(), results.end(), host_results.begin(), queue);
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BOOST_CHECK((host_matrices[0] * host_vectors[0]) == host_results[0]);
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BOOST_CHECK((host_matrices[1] * host_vectors[1]) == host_results[1]);
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BOOST_CHECK((host_matrices[2] * host_vectors[2]) == host_results[2]);
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BOOST_CHECK((host_matrices[3] * host_vectors[3]) == host_results[3]);
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}
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BOOST_AUTO_TEST_SUITE_END()
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