[Computer-go] What hardware to use to train the DNN

Hiroshi Yamashita yss at bd.mbn.or.jp
Tue Feb 2 10:55:09 PST 2016


Hi David,

I use GTS 450 and GTX 980. I use Caffe on ubuntu 14.04.
Caffe's install is difficult. So I recommend using ubuntu 14.04.

time for predicting a position

               Detlef44%     Detlef54%   CUDA cores   clock
GTS 450         17.2ms         21  ms       192      783MHz
GTX 980          5.1ms         10.1ms     2,048     1126MHz
GTX 980 cuDNN    6.4ms          5.9ms     2,048     1126MHz
GTX 670          7.9ms                    1,344      915MHz

Learning time

                MNIST GPU     Aya's 10000 iteration (mini-batch=256)
GTS 450           306 sec       9720 sec
GTX 980           169 sec
GTX 980 cuDNN      24 sec        726 sec

GTS 450 is not so slow for predicting a position.
But GTX 980 learning speed is 13 times faster than GTS 450.
And cuDNN, library provided by NVIDIA, is very effective.
cuDNN does not work on GTS 450.
And caffe's page is nice.
http://caffe.berkeleyvision.org/performance_hardware.html

Regards,
Hiroshi Yamashita


----- Original Message ----- 
From: "David Fotland" <fotland at smart-games.com>
To: <computer-go at computer-go.org>
Sent: Wednesday, February 03, 2016 3:25 AM
Subject: [Computer-go] What hardware to use to train the DNN


> Detlef, Hiroshi, Hideki, and others,
>
> I have caffelib integrated with Many Faces so I can evaluate a DNN.  Thank you very much Detlef for sample code to set up the 
> input layer.  Building caffe on windows is painful.  If anyone else is doing it and gets stuck I might be able to help.
>
> What hardware are you using to train networks?  I don’t have a cuda-capable GPU yet, so I'm going to buy a new box.  I'd like 
> some advice.  Caffe is not well supported on Windows, so I plan to use a Linux box for training, but continue to use Windows for 
> testing and development.  For competitions I could use either windows or linux.
>
> Thanks in advance,
>
> David 




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