Looks like you're making good progress. Apart from the time gained training, you'll probably get a similar speed up when using the DNN during play? I'm curious when you'll see improvement in play outweigh the extra computational cost.
Mark > On Apr 26, 2016, at 9:55 PM, David Fotland <fotl...@smart-games.com> wrote: > > I have my deep neural net training setup working, and it's working so well I > want to share. I already had Caffe running on my desktop machine (4 core > i7) without a GPU, with inputs similar to AlphaGo generated by Many Faces > into an LMDB database. I trained a few small nets for a day each to get > some feel for it. > > I bought an Alienware Area 51 from Dell, with two GTX 980 TI GPUs, 16 GB of > memory, and 2 TB of disk. I set it up to dual boot Ubuntu 14.04, which made > it trivial to get the latest caffe up and running with CUDNN. 2 TB of disk > is not enough. I'll have to add another drive. > > I expected something like 20x speedup on training, but I was shocked by what > I actually got. > > On my desktop, the Caffe MNIST sample took 27 minutes to complete. On the > new machine it was 22 seconds. 73x faster. > > My simple network has 42 input planes, and 4 layers of 48 filters each. > Training runs about 100x faster on the Alienware. Training 100k Caffe > iterations (batches) of 50 positions takes 13 minutes, rather than almost a > full day on my desktop. > > David > > _______________________________________________ > 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
