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https://github.com/boostorg/compute
A C++ GPU Computing Library for OpenCL
https://github.com/boostorg/compute
boost c-plus-plus compute cpp gpgpu gpu hpc opencl performance
Last synced: 3 days ago
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A C++ GPU Computing Library for OpenCL
- Host: GitHub
- URL: https://github.com/boostorg/compute
- Owner: boostorg
- License: bsl-1.0
- Created: 2013-03-02T20:15:58.000Z (almost 12 years ago)
- Default Branch: master
- Last Pushed: 2024-08-22T14:55:45.000Z (4 months ago)
- Last Synced: 2024-10-29T15:37:53.444Z (about 2 months ago)
- Topics: boost, c-plus-plus, compute, cpp, gpgpu, gpu, hpc, opencl, performance
- Language: C++
- Homepage: http://boostorg.github.io/compute/
- Size: 8.33 MB
- Stars: 1,552
- Watchers: 110
- Forks: 333
- Open Issues: 156
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE_1_0.txt
Awesome Lists containing this project
README
# Boost.Compute #
[](https://travis-ci.org/boostorg/compute)
[](https://ci.appveyor.com/project/jszuppe/compute/branch/master)
[](https://coveralls.io/r/boostorg/compute)
[](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 ([email protected]) for more information.