[Numpy-discussion] Fwd: GPU Numpy

Rohit Garg rpg.314@gmail....
Thu Sep 10 11:19:28 CDT 2009


> Yes. However, it is worth making the distinction between
> embarrassingly parallel problems and SIMD problems. Not all
> embarrassingly parallel problems are SIMD-capable. GPUs do SIMD, not
> generally embarrassing problems.

GPUs exploit both dimensions of parallelism, both simd (aka
vectorization) and parallelization (aka multicore). And yeah, 99.9% of
the time branching on GPU should be the least/last of your worries if
your problem is data-parallel. There are much worse things than
branchings.

As for SIMD  special functions, branching can certainly be eliminated.
I have written/come across some special functions myself, and I do not
know any case which is difficult to do efficiently on a gpu.
Certainly, I know less than some folks around here. May be you can
contribute a counter example to this discussion.

Regards,

-- 
Rohit Garg

http://rpg-314.blogspot.com/

Senior Undergraduate
Department of Physics
Indian Institute of Technology
Bombay


More information about the NumPy-Discussion mailing list