I'll keep it in mind.  I'm using caffe, which has a compile-time flag, so I'm 
not sure it will work with GPU enabled on a machine without a GPU.

David

> -----Original Message-----
> From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf
> Of Michael Markefka
> Sent: Tuesday, March 01, 2016 2:21 PM
> To: computer-go@computer-go.org
> Subject: Re: [Computer-go] Deep Zen - do we have a race now?
> 
> Would be nice to have it as an option. My desktop PC and my laptop both
> have CUDA-enabled graphics, and that isn't uncommon anymore.
> 
> Also, if you are training on a GPU you can probably avoid a lot of
> hassle if you expect to run it on a GPU as well. I don't know how other
> NN implementations handle it, but the GPU-to-CPU conversion script that
> comes with the Theano-based pylearn2 kit doesn't work very reliably.
> 
> Also, even quite big nets probably can be run on modest GPUs reasonably
> well (within memory bounds). It's the training where the size really
> hurts.
> 
> On Tue, Mar 1, 2016 at 6:19 PM, Petr Baudis <pa...@ucw.cz> wrote:
> > On Tue, Mar 01, 2016 at 09:14:39AM -0800, David Fotland wrote:
> >> Very interesting, but it should also mention Aya.
> >>
> >> I'm working on this as well, but I haven t bought any hardware yet.
> My goal is not to get 7 dan on expensive hardware, but to get as much
> strength as I can on standard PC hardware.  I'll be looking at much
> smaller nets, that don t need a GPU to run.  I'll have to buy a GPU for
> training.
> >
> > But I think most people who play Go are also fans of computer games
> > that often do use GPUs. :-)  Of course, it's something totally
> > different from NVidia Keplers, but still the step up from a CPU is
> tremendous.
> >
> >                                 Petr Baudis
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