compute

Every library benchmarked in there is open source. - https://github.com/arrayfire/arrayfire - https://github.com/thrust/thrust - https://github.com/boostorg/compute - https://github.com/HSA-Libraries/Bolt - https://www.threadingbuildingblocks.org/download Which library did you think is proprietary?

I'm working on an open-source C++ library for GPGPU/parallel-computing based on OpenCL called Boost.Compute. Check it out here: https://github.com/kylelutz/compute

Boost.Compute (https://github.com/kylelutz/compute) is a C++ GPGPU based on OpenCL. We're always looking for more contributors with knowledge of C++ and an interest in GPU computing.

If you're using C++, check out Boost.Compute [1]. It provides a high-level STL-like API for OpenCL (without preventing you from directly using the low-level OpenCL APIs). It simplifies common tasks such as copying data to/from the device and also provides a number of built-in algorithms (e.g. sorting/reducing/transforming, etc). [1] https://github.com/kylelutz/compute

Would you be interested in trying to adapt some of your approaches into a C++ GPGPU library (https://github.com/kylelutz/compute)?

There is also VexCL [0] and Boost.Compute [1]. Both are quite capable. I myself am working on something similar - it is called Aura but still a long way to go [2]. ViennaCL, VexCL and Boost.Compute focus on maximizing programmer productivity. Converting existing code from i.e. Matlab to accelerator hardware is trivial using these libraries and you get excellent performance quickly. Furthermore, NT2 doesn't get nearly as much publicity as it deserves [3]. Not only does it provide an incredible number of functions ready to use, but it also exploits the vector processing capabilities of modern CPUs. These capabilities are too often ignored by developers or left for non-optimal compiler optimizations to exploit. In my own library Aura, I focus on maximizing performance (over developer convenience). The target audience are developers of real-t

Boost.Compute (https://github.com/kylelutz/compute) - A C++ GPU Computing Library for OpenCL It's cool because it offers C++ developers an easy path to running code on GPUs and multi-core CPUs via an STL-like API. It's similar to NVIDIA's Thrust library but supports all OpenCL compatible devices (including AMD GPUs and Intel CPUs/accelerators). Documentation is here: http://kylelutz.github.io/compute/ P.S. It's still under active development and we're looking for more contributors with an interest in parallel computing and C++. Send me an e-mail if you're interested!