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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