Caffe looks like it runs the same net on CPU and GPU with no conversion.  I'm 
going to see if I can get it working on an AWS GPU instance this weekend.

David

> -----Original Message-----
> From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf
> Of Michael Markefka
> Sent: Wednesday, March 02, 2016 12:27 AM
> To: computer-go@computer-go.org
> Subject: Re: [Computer-go] Deep Zen - do we have a race now?
> 
> Hi Petr,
> 
> to clarify a bit:
> 
> pylearn2 specifically comes with a script to convert a model trained on
> a GPU into a version that runs on the CPU. This doesn't work very well
> though and the documentation points that out too. According to the dev
> commens that is down to how Theano, the framework pylearn2 is based on,
> handles its shared variables und the CUDA variables need to be converted
> to Theano tensor variables.
> 
> Just wanted to advise caution that this process working flawlessly isn't
> necessarily given in every NN lib. If Caffe does this well, then David
> shouldn't have any problem of course and this warning doesn't apply
> here.
> 
> -Michael
> 
> On Wed, Mar 2, 2016 at 8:57 AM, Petr Baudis <pa...@ucw.cz> wrote:
> > On Tue, Mar 01, 2016 at 02:51:03PM -0800, David Fotland wrote:
> >> > 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.
> >> 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.
> >
> > I'm not sure about Michael's specific problem, but in my experience,
> > there is no trouble at all transferring stuff between CPU and GPU -
> > your model is, after all, just the weight matrices.  In Caffe, you
> > should be able to switch between GPU and CPU completely freely.
> >
> >                                 Petr Baudis
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