Re: [Boost-users] Boost.Compute v0.1 Released

Hello Kyle, On 17 March 2014 00:03, Kyle Lutz wrote:

I'm proud to announce the initial release (version 0.1) of Boost.Compute! It is available on GitHub [1] and instructions for using the library can be found in the documentation [2].

Boost.Compute is a GPGPU and parallel-programming library based on OpenCL. It provides an STL-like API and implements many common containers (e.g. vector<T>, array) as well as many common algorithms (e.g. sort(), accumulate(), transform()). A full list can be found in the header reference [3].

I hope to propose Boost.Compute for review in the next few months but for I'm looking for more wide-spread testing and feedback from the Boost community (please note the FAQ [4] and design rationale [5] where I hope to have answered some common questions).

Thanks, Kyle

[1] https://github.com/kylelutz/compute [2] http://kylelutz.github.io/compute/ [3] http://kylelutz.github.io/compute/compute/reference.html [4] http://kylelutz.github.io/compute/boost_compute/faq.html [5] http://kylelutz.github.io/compute/boost_compute/design.html _______________________________________________ Boost-users mailing list Boost-users@lists.boost.org http://lists.boost.org/mailman/listinfo.cgi/boost-users

I am looking forward to try this out. I have a couple of questions: - how do the algorithms compare performance-wise with similar CUDA libraries? I remember trying Boost.Compute in the early days and IIRC there was quite a performance gap. Would it be possible to add a performance section to the documentation? - Are you planning any support for multi-device computations? In my experience, available memory can be quite a bottleneck on GPUs, and having support for muti-device computations (i.e., multiple GPUs but also GPUs/CPU hybrids) would be quite handy. I am happy to see this kind of work happening in OpenCL and Boost land, and I really like the STL-like design of the library. Cheers, Francesco.