On Fri, Apr 11, 2014 at 3:34 PM, Dean Wampler <[email protected]> wrote:
> I've thought about this idea, although I haven't tried it, but I think the > right approach is to pick your granularity boundary and use Spark + JVM for > large-scale parts of the algorithm, then use the gpgus API for number > crunching large chunks at a time. No need to run the JVM and Spark on the > GPU, which would make no sense anyway. > > I find that would be crazy to be able to run the JVM on a GPU even if it's a bit non-sense XD Anyway, you're right, the approach by delegating just some parts of the code to the GPU is interesting but it also means you have to pre-install this code on all cluster nodes... > Here's another approach: > http://www.cakesolutions.net/teamblogs/2013/02/13/akka-and-cuda/ > > dean > > > On Fri, Apr 11, 2014 at 7:49 AM, Saurabh Jha > <[email protected]>wrote: > >> There is a scala implementation for gpgus (nvidia cuda to be precise). >> but you also need to port mesos for gpu's. I am not sure about mesos. Also, >> the current scala gpu version is not stable to be used commercially. >> >> Hope this helps. >> >> Thanks >> saurabh. >> >> >> >> *Saurabh Jha* >> Intl. Exchange Student >> School of Computing Engineering >> Nanyang Technological University, >> Singapore >> Web: http://profile.saurabhjha.in >> Mob: +65 94663172 >> >> >> On Fri, Apr 11, 2014 at 8:40 PM, Pascal Voitot Dev < >> [email protected]> wrote: >> >>> This is a bit crazy :) >>> I suppose you would have to run Java code on the GPU! >>> I heard there are some funny projects to do that... >>> >>> Pascal >>> >>> On Fri, Apr 11, 2014 at 2:38 PM, Jaonary Rabarisoa <[email protected]>wrote: >>> >>>> Hi all, >>>> >>>> I'm just wondering if hybrid GPU/CPU computation is something that is >>>> feasible with spark ? And what should be the best way to do it. >>>> >>>> >>>> Cheers, >>>> >>>> Jaonary >>>> >>> >>> >> > > > -- > Dean Wampler, Ph.D. > Typesafe > @deanwampler > http://typesafe.com > http://polyglotprogramming.com >
