[Beowulf] any gp-gpu clusters?

Massimiliano Fatica mfatica at gmail.com
Sat Jun 23 10:26:40 PDT 2007

Mark,I am messing up with a GPU oriented cluster.

I am now on travel to ISC, where I will show a sustained Teraflop with a
workstation with 4 Tesla cards using VMD to do ion placement (for the list
member going to Dresden stop by to the Nvidia booth to see the demo in
action). This was a computation that used to take 100 CPU hours on an Altix
and it is now done in the matter of minutes. Yes, the whole system probably
consumes 900W ( the tdp of a tesla is 170W not 220W), but I can assure you
that is nothing compared to a big Altix machine and you can put under your
desk and do some real science.

Several groups are building gpu-oriented cluster. Once mine is completed ( 8
compute nodes, each one with 2 Tesla boards) , it should be accessible for
testing to academic and research group. People interested in testing their
CUDA codes on cluster could drop me an email.

On a side note, it is interesting to see all the speculations from people
that have never used CUDA (and most of the time don't have a clue...) and at
the same time to see quality software (mostly open source like VMD, NAMD,
SOFA ) achieving pretty impressive results and enabling new science.

PS:  Usual disclaimer, I work in the GPU Computing group at NVIDIA.

On 6/21/07, Mark Hahn <hahn at mcmaster.ca> wrote:
> Hi all,
> is anyone messing with GPU-oriented clusters yet?
> I'm working on a pilot which I hope will be something
> like 8x workstations, each with 2x recent-gen gpu cards.
> the goal would be to host cuda/rapidmind/ctm-type gp-gpu development.
> part of the motive here is just to create a gpu-friendly
> infrastructure into which commodity cards can be added and
> refreshed every 8-12 months.  as opposed to "investing" in
> quadro-level cards which are too expensive enough to toss when obsoleted.
> nvidia's 1U tesla (with two g80 chips) looks potentially attractive,
> though I'm guessing it'll be premium/quadro-priced - not really in
> keeping with the hyper-moore's-law mantra...
> if anyone has experience with clustered gp-gpu stuff, I'm interested
> in comments on particular tools, experiences, configuration of the host
> machines and networks, etc.  for instance, is it naive to think that
> gp-gpu is most suited to flops-heavy-IO-light apps, and therefore doesn't
> necessarily need a hefty (IB, 10Geth) network?
> thanks, mark hahn.
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