Re: [boost] [compute] GPGPU Library - Request For Feedback

Subject: Re: [boost] [compute] GPGPU Library - Request For Feedback
From: Kyle Lutz (kyle.r.lutz_at_[hidden])
Date: 2013-03-07 22:17:53

On Thu, Mar 7, 2013 at 2:18 PM, Evgeny Panasyuk
<evgeny.panasyuk_at_[hidden]> wrote:
> 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