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
