[Beowulf] GPU question

amjad ali amjad11 at gmail.com
Sat Aug 29 16:35:30 PDT 2009


Hello all, specially Gil Brandao

Actually I want to start CUDA programming for my |C.I have 2 options to do:
1) Buy a new PC that will have 1 or 2 CPUs and 2 or 4 GPUs.
2) Add 1 GPUs to each of the Four nodes of my PC-Cluster.

Which one is more "natural" and "practical" way?
Does a program written for any one of the above will work fine on the other?
or we have to re-program for the other?

Regards.

On Sat, Aug 29, 2009 at 5:48 PM, <madskaddie at gmail.com> wrote:

> On Sat, Aug 29, 2009 at 8:42 AM, amjad ali<amjad11 at gmail.com> wrote:
> > Hello All,
> >
> >
> >
> > I perceive following computing setups for GP-GPUs,
> >
> >
> >
> > 1)      ONE PC with ONE CPU and ONE GPU,
> >
> > 2)      ONE PC with more than one CPUs and ONE GPU
> >
> > 3)      ONE PC with one CPU and more than ONE GPUs
> >
> > 4)      ONE PC with TWO CPUs (e.g. Xeon Nehalems) and more than ONE GPUs
> > (e.g. Nvidia C1060)
> >
> > 5)      Cluster of PCs with each node having ONE CPU and ONE GPU
> >
> > 6)      Cluster of PCs with each node having more than one CPUs and ONE
> GPU
> >
> > 7)      Cluster of PCs with each node having ONE CPU and more than ONE
> GPUs
> >
> > 8)      Cluster of PCs with each node having more than one CPUs and more
> > than ONE GPUs.
> >
> >
> >
> > Which of these are good/realistic/practical; which are not? Which are
> quite
> > “natural” to use for CUDA based programs?
> >
>
> CUDA is kind of new technology, so I don't think there is a "natural
> use" yet, though I read that there people doing CUDA+MPI and there are
> papers on CPU+GPU algorithms.
>
> >
> > IMPORTANT QUESTION: Will a cuda based program will be equally good for
> > some/all of these setups or we need to write different CUDA based
> programs
> > for each of these setups to get good efficiency?
> >
>
> There is no "one size fits all" answer to your question. If you never
> developed with CUDA, buy one GPU an try it. If it fits your problems,
> scale it with the approach that makes you more comfortable (but
> remember that scaling means: making bigger problems or having more
> users). If you want a rule of thumb: your code must be
> _truly_parallel_. If you are buying for someone else, remember that
> this is a niche. The hole thing is starting, I don't thing there isn't
> many people that needs much more 1 or 2 GPUs.
>
> >
> > Comments are welcome also for AMD/ATI FireStream.
> >
>
> put it on hold until OpenCL takes of  (in the real sense, not in
> "standards papers" sense), otherwise you will have to learn another
> technology that even fewer people knows.
>
>
> Gil Brandao
>
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