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- //---------------------------------------------------------------------------//
- // Copyright (c) 2013-2014 Kyle Lutz <kyle.r.lutz@gmail.com>
- //
- // Distributed under the Boost Software License, Version 1.0
- // See accompanying file LICENSE_1_0.txt or copy at
- // http://www.boost.org/LICENSE_1_0.txt
- //
- // See http://boostorg.github.com/compute for more information.
- //---------------------------------------------------------------------------//
- #include <iostream>
- #include <Eigen/Core>
- #include <Eigen/LU>
- #include <boost/compute/function.hpp>
- #include <boost/compute/system.hpp>
- #include <boost/compute/algorithm/transform.hpp>
- #include <boost/compute/container/vector.hpp>
- #include <boost/compute/types/fundamental.hpp>
- namespace compute = boost::compute;
- // this example shows how to compute the determinant of many 4x4 matrices
- // using a determinant function and the transform() algorithm. in OpenCL the
- // float16 type can be used to store a 4x4 matrix and the components are laid
- // out in the following order:
- //
- // M = [ s0 s4 s8 sc ]
- // [ s1 s5 s9 sd ]
- // [ s2 s6 sa se ]
- // [ s3 s7 sb sf ]
- //
- // the input matrices are created using eigen's random matrix and then
- // used again at the end to verify the results of the determinant function.
- int main()
- {
- // get default device and setup context
- compute::device gpu = compute::system::default_device();
- compute::context context(gpu);
- compute::command_queue queue(context, gpu);
- std::cout << "device: " << gpu.name() << std::endl;
- size_t n = 1000;
- // create random 4x4 matrices on the host
- std::vector<Eigen::Matrix4f> matrices(n);
- for(size_t i = 0; i < n; i++){
- matrices[i] = Eigen::Matrix4f::Random();
- }
- // copy matrices to the device
- using compute::float16_;
- compute::vector<float16_> input(n, context);
- compute::copy(
- matrices.begin(), matrices.end(), input.begin(), queue
- );
- // function returning the determinant of a 4x4 matrix.
- BOOST_COMPUTE_FUNCTION(float, determinant4x4, (const float16_ m),
- {
- return m.s0*m.s5*m.sa*m.sf + m.s0*m.s6*m.sb*m.sd + m.s0*m.s7*m.s9*m.se +
- m.s1*m.s4*m.sb*m.se + m.s1*m.s6*m.s8*m.sf + m.s1*m.s7*m.sa*m.sc +
- m.s2*m.s4*m.s9*m.sf + m.s2*m.s5*m.sb*m.sc + m.s2*m.s7*m.s8*m.sd +
- m.s3*m.s4*m.sa*m.sd + m.s3*m.s5*m.s8*m.se + m.s3*m.s6*m.s9*m.sc -
- m.s0*m.s5*m.sb*m.se - m.s0*m.s6*m.s9*m.sf - m.s0*m.s7*m.sa*m.sd -
- m.s1*m.s4*m.sa*m.sf - m.s1*m.s6*m.sb*m.sc - m.s1*m.s7*m.s8*m.se -
- m.s2*m.s4*m.sb*m.sd - m.s2*m.s5*m.s8*m.sf - m.s2*m.s7*m.s9*m.sc -
- m.s3*m.s4*m.s9*m.se - m.s3*m.s5*m.sa*m.sc - m.s3*m.s6*m.s8*m.sd;
- });
- // calculate determinants on the gpu
- compute::vector<float> determinants(n, context);
- compute::transform(
- input.begin(), input.end(), determinants.begin(), determinant4x4, queue
- );
- // check determinants
- std::vector<float> host_determinants(n);
- compute::copy(
- determinants.begin(), determinants.end(), host_determinants.begin(), queue
- );
- for(size_t i = 0; i < n; i++){
- float det = matrices[i].determinant();
- if(std::abs(det - host_determinants[i]) > 1e-6){
- std::cerr << "error: wrong determinant at " << i << " ("
- << host_determinants[i] << " != " << det << ")"
- << std::endl;
- return -1;
- }
- }
- return 0;
- }
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