Interoperability with other librariesΒΆ

VexCL does not try (too hard) to hide the implementation details from the user. For example, in case of the OpenCL backend VexCL is based on the Khronos C++ API, and the underlying OpenCL types are easily accessible. Hence, it should be easy to interoperate with other OpenCL libraries. Similarly, in case of the CUDA backend, VexCL backend types are thin wrappers around CUDA Driver API.

When Boost.Compute backend is used, VexCL is based on the core classes of the Boost.Compute library. It is very easy to apply Boost.Compute algorithms to VexCL vectors and to use Boost.Compute buffers within VexCL expressions.

Here is an example:

#include <iostream>
#include <boost/compute.hpp>

#include <vexcl/vexcl.hpp>

namespace compute = boost::compute;

int main() {
    compute::command_queue bcq = compute::system::default_queue();

    const int n = 16;

    // Use boost.compute queue to allocate VexCL vectors:
    vex::vector<int> x({bcq}, n);
    x = 2 * vex::element_index();

    // Wrap boost.compute vectors into vexcl vectors (no data is copied):
    compute::vector<int> bcv(n, bcq.get_context());
    vex::vector<int> y({bcq}, bcv.get_buffer());
    y = x * 2;

    // Apply Boost.Compute algorithm to a vexcl vector:
        compute::make_buffer_iterator<int>(x(0).raw_buffer(), 0),
        compute::make_buffer_iterator<int>(x(0).raw_buffer(), n)