Hi Andreas,
On Tue, Apr 5, 2011 at 1:27 PM, Andreas Kloeckner
<[email protected]> wrote:
> In principle, I'm open to the idea of a CUDA/CL abstraction layer. I
> don't think this would have a measurable performance impact, but we
> *should* back up that claim that if we decide to make one.
>
> What kept me from making one is that the two sets of launch logic are
> sufficiently non-alike (CUDA dealing with cache size bits, CL adapting
> to Apple specifics, CL dealing with wait_fors (it doesn't yet, but it
> needs to)...) that I thought the having two different invocation codes
> might not be such a horrible idea. Perhaps the right recipe would be to
> try and gradually move the two codes towards using a common set of
> functions, before trying to go whole-hog and unify them entirely.
>
> I also noticed that you have two sets of launch logic in PyFFT--what was
> your reasoning behind that?
Pyfft has two thin wrappers for Cuda/CL contexts, modules and kernels,
just to avoid writing constructions like this one everywhere:
if Cuda:
context.synchronize()
else:
context.finish()
Of course, in pyfft case all kernel invocations are quite similar,
which allowed me to create the simple abstraction. I guess it will not
be that easy in general case.
> That might not be such a bad idea. It makes us rely more heavily on
> Python's dependency handling, but I suppose that's ok. I've registered a
> PyPI project for this:
>
> http://pypi.python.org/pypi/compyte
>
> (fairly empty) git tree at:
> http://git.tiker.net/trees/compyte.git
>
> (I'm shooting for, e.g., 'compyte.primitives.scan'. :)
>
> I'll probably release the 2011.1 versions of PyCUDA and PyOpenCL without
> this, but we can look at unifying this afterwards.
Yes, I think I'll try to implement RNG in compyte and see how this
goes. By the way, it would be nice to have this repo mirrored on
github; I think it provides quite a convenient interface for
collaboration.
Best regards,
Bogdan
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