Also, reading more of that pull request, the guy benchmarking it had old nvidia driver version which came with about 50% performance hit. So I'm not sure what were the final numbers. (And whether current caffe version can actually match these numbers, since this pull request wasn't merged.)
On Wed, Mar 02, 2016 at 12:29:41AM -0800, Chaz G. wrote: > Rémi, > > Nvidia launched the K20 GPU in late 2012. Since then, GPUs and their > convolution algorithms have improved considerably, while CPU performance > has been relatively stagnant. I would expect about a 10x improvement with > 2016 hardware. > > When it comes to training, it's the difference between running a job > overnight and running a job for the entire weekend. > > Best, > -Chaz > > On Tue, Mar 1, 2016 at 1:03 PM, Rémi Coulom <remi.cou...@free.fr> wrote: > > > How tremendous is it? On that page, I find this data: > > > > https://github.com/BVLC/caffe/pull/439 > > > > " > > These are setup details: > > > > * Desktop: CPU i7-4770 (Haswell), 3.5 GHz , DRAM - 16 GB; GPU K20. > > * Ubuntu 12.04; gcc 4.7.3; MKL 11.1. > > > > Test:: imagenet, 100 train iteration (batch = 256). > > > > * GPU: time= 260 sec / memory = 0.8 GB > > * CPU: time= 752 sec / memory = 3.5 GiB //Memory data is from system > > monitor. > > > > " > > > > This does not look so tremendous to me. What kind of speed difference do > > you get for Go networks? > > > > Rémi > > > > On 03/01/2016 06:19 PM, Petr Baudis 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 > >> _______________________________________________ > >> Computer-go mailing list > >> Computer-go@computer-go.org > >> http://computer-go.org/mailman/listinfo/computer-go > >> > > > > _______________________________________________ > > Computer-go mailing list > > Computer-go@computer-go.org > > http://computer-go.org/mailman/listinfo/computer-go > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go -- Petr Baudis If you have good ideas, good data and fast computers, you can do almost anything. -- Geoffrey Hinton _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
