A C++ GPU Computing Library for OpenCL # Boost.Compute # [![Build Status](https://travis-ci.org/boostorg/compute.svg?branch=master)](https://travis-ci.org/boostorg/compute) [![Build status](https://ci.appveyor.com/api/projects/status/4s2nvfc97m7w23oi/branch/master?svg=true)](https://ci.appveyor.com/project/jszuppe/compute/branch/master) [![Coverage Status](https://coveralls.io/repos/boostorg/compute/badge.svg?branch=master)](https://coveralls.io/r/boostorg/compute) [![Gitter](https://badges.gitter.im/boostorg/compute.svg)](https://gitter.im/boostorg/compute?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) Boost.Compute is a GPU/parallel-computing library for C++ based on OpenCL. The core library is a thin C++ wrapper over the OpenCL API and provides access to compute devices, contexts, command queues and memory buffers. On top of the core library is a generic, STL-like interface providing common algorithms (e.g. `transform()`, `accumulate()`, `sort()`) along with common containers (e.g. `vector`, `flat_set`). It also features a number of extensions including parallel-computing algorithms (e.g. `exclusive_scan()`, `scatter()`, `reduce()`) and a number of fancy iterators (e.g. `transform_iterator<>`, `permutation_iterator<>`, `zip_iterator<>`). The full documentation is available at http://boostorg.github.io/compute/. ## Example ## The following example shows how to sort a vector of floats on the GPU: ```c++ #include #include #include namespace compute = boost::compute; int main() { // get the default compute device compute::device gpu = compute::system::default_device(); // create a compute context and command queue compute::context ctx(gpu); compute::command_queue queue(ctx, gpu); // generate random numbers on the host std::vector host_vector(1000000); std::generate(host_vector.begin(), host_vector.end(), rand); // create vector on the device compute::vector device_vector(1000000, ctx); // copy data to the device compute::copy( host_vector.begin(), host_vector.end(), device_vector.begin(), queue ); // sort data on the device compute::sort( device_vector.begin(), device_vector.end(), queue ); // copy data back to the host compute::copy( device_vector.begin(), device_vector.end(), host_vector.begin(), queue ); return 0; } ``` Boost.Compute is a header-only library, so no linking is required. The example above can be compiled with: `g++ -I/path/to/compute/include sort.cpp -lOpenCL` More examples can be found in the [tutorial]( http://boostorg.github.io/compute/boost_compute/tutorial.html) and under the [examples](https://github.com/boostorg/compute/tree/master/example) directory. ## Support ## Questions about the library (both usage and development) can be posted to the [mailing list](https://groups.google.com/forum/#!forum/boost-compute). Bugs and feature requests can be reported through the [issue tracker]( https://github.com/boostorg/compute/issues?state=open). Also feel free to send me an email with any problems, questions, or feedback. ## Help Wanted ## The Boost.Compute project is currently looking for additional developers with interest in parallel computing. Please send an email to Kyle Lutz (kyle.r.lutz@gmail.com) for more information. Source: https://github.com/boostorg/compute

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