Am 17.03.14 01:11, schrieb Matt Calabrese:

Awesome!

On Sun, Mar 16, 2014 at 5:03 PM, Kyle Lutz mailto:kyle.r.lutz@gmail.com> 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].

Yes, this is most interesting! Best Regards, beet

On Sun, Mar 16, 2014 at 6:10 PM, Rhys Ulerich wrote:

On Sun, Mar 16, 2014 at 7:03 PM, Kyle Lutz wrote:

...

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].

Besides the OpenGL niceness and STLishness, is there a reason to prefer Boost.Compute over alternatives targeted at OpenCL/CUDA numerics? There's already been much work in this space [1], including VexCL [2] which many of my collaborators like. While there is an answer in the FAQ [3], it seems dodgy as clearly VexCL could not presently be built on Boost.Compute since the latter does not support for CUDA while the former does.

Good point. That FAQ entry was written before VexCL added its CUDA back-end (which occurred relatively recently). Boost.Compute and VexCL have different aims and scopes. Boost.Compute is more similar to the C++ STL while VexCL is more similar to a linear algebra library like Eigen. Also see this StackOverflow question [1] entitled "Differences between VexCL, Thrust, and Boost.Compute". -kyle [1] http://stackoverflow.com/questions/20154179/differences-between-vexcl-thrust...

Hi, I am the developer of VexCL :). On Mon, Mar 17, 2014 at 7:43 PM, Rhys Ulerich wrote:

Hi Kyle

...

Good point. That FAQ entry was written before VexCL added its CUDA back-end (which occurred relatively recently). Boost.Compute and VexCL have different aims and scopes. Boost.Compute is more similar to the C++ STL while VexCL is more similar to a linear algebra library like Eigen. Also see this StackOverflow question [1] entitled "Differences between VexCL, Thrust, and Boost.Compute".

[1] http://stackoverflow.com/questions/20154179/differences-between-vexcl-thrust...

Thank you for the information.

I have updated the answer on stackoverflow following Gonzalo's comment above about unavailability of easy interaction with user-defined functors and lambdas. I'll duplicate it here for convenience: Update: @gnzlbg commented that there is no support for C++ functors and lambdas in OpenCL-based libraries. And indeed, OpenCL is based on C99 and is compiled from sources stored in strings at runtime, so there is no easy way to fully interact with C++ classes. But to be fare, OpenCL-based libraries do support user-based functions and even lambdas to some extent. - Boost.Compute provides its own implementation of simple lambdashttp://kylelutz.github.io/compute/boost_compute/advanced_topics.html#boost_c... (based on Boost.Proto), and allows to interact with user-defined structs through BOOST_COMPUTE_ADAPT_STRUCThttp://kylelutz.github.io/compute/BOOST_COMPUTE_ADAPT_STRUCT.html andBOOST_COMPUTE_CLOSUREhttp://kylelutz.github.io/compute/BOOST_COMPUTE_CLOSURE.html macros. - VexCL provides linear-algebra-like DSL (also based on Boost.Proto), and also supports conversion of generic C++ algorithms and functorshttps://github.com/ddemidov/vexcl#converting-generic-c-algorithms-to-opencl (and even Boost.Phoenix lambdas) to OpenCL functions (with restrictions). - I believe AMD's Bolt does supports user-defined functors through its "C++ for OpenCL" extension magic. Having said that, CUDA-based libraries (and may be C++ AMP) have an obvious advantage of actual compile-time compiler (can you even say that?), so the integration with user code can be much tighter. Another point is that when you have an AMD GPU (which generally provide more performance per dollar), then more advanced CUDA compiler has zero advantages :). I do believe that there is a place for a library (such as Boost.Compute) that would provide a set of standard accelerated algorithms. I missed such a library a few times while implementing VexCL. But Kyle, before you propose Boost.Compute for the inclusion into Boost (I think you should really do that!) you should make sure that the provided algorithms perform on par with the other libraries (e.g. Thrust) on the same hardware (I did not compare the performances, so this could be the case already). -- Cheers, Denis