On Thu, Mar 7, 2013 at 2:18 PM, Evgeny Panasyuk
It looks like this library is some kind of abstraction around OpenCL. But as I can see, it does not offer ways to abstract from OpenCL kernels syntax in general way: https://github.com/kylelutz/compute/blob/master/example/monte_carlo.cpp . I.e. not just simple things like boost::compute::sqrt, or simple lambda expressions like "_1 * 3 - 4".
Kernel description can be abstracted in several ways:
1) Approach similar to Boost.Phoenix - generate OpenCL kernel code based on gathered expression tree.
2) Approach similar to TaskGraph library: http://www3.imperial.ac.uk/pls/portallive/docs/1/45421696.PDF - describe kernel in terms of special function calls, macros, expression templates and so on. Actual kernel is generated when that description code is "executed". Here is small demo - http://ideone.com/qQ4Pvo (check output at bottom).
This is the direction I would like to go with the library. However, coming up with a nice general solution for specifying kernel code in C++ is quite tricky. If you have example code for a potential API I'd love to take a look. For now, the only two exposed ways of using custom functions is directly specifying the OpenCL code (like in the monte_carlo example) or using the lambda expression framework. In the short-term future I am looking at also allowing bind() like functions to compose multiple built-in functions along with literal values. Internally there is also the meta_kernel class which is a hybrid of C++ code and raw OpenCL C code strings which is used by the algorithms to implement generic kernels. This may one day be cleaned-up and promoted to the public API but for now it is an implementation detail. I have been planning on making more use of Boost.Phoenix as you suggested. Thanks for posting the TaskGraph paper. It looks very interesting and I will take a closer look when I get some spare time. Cheers, Kyle