Try to use Theano profiling to know where the time is spent. Le jeu. 11 mai 2017 15:48, Gavin Weiguang Ding <gavin.w.d...@gmail.com> a écrit :
> hi daksh, > > have you figured out the difference? i have the same issue here. > > Thanks, > Gavin > > > On Friday, 17 February 2017 02:37:00 UTC-5, Daksh Varshneya wrote: >> >> Hi, >> >> I have a piece of code which basically trains a GRU to learn from some >> sequences. I am training the neural network on each individual >> sequence(batch size = 1). When I am running the training code on my local >> machine which has a Nvidia gtx 960m, it takes about 3.09 secs for ~ 10 data >> points. But when I run the same code on aws ec2 p2.xlarge machine which has >> a Nvidia Tesla K80 GPU, surprisingly the time taken for exactly same >> sequences is around 4.93 seconds. This is very disheartening right now. I >> have tried switching AMI's as well. Originally I used a clean install of >> ubuntu 14.04 and installed cuda, cudnn and theano myself. The second image >> I took from amazon marketplace which had all these things installed. >> The code is exactly the same with no difference at all. Any pointers >> which can help? >> >> Thanks, >> Daksh >> > -- > > --- > You received this message because you are subscribed to the Google Groups > "theano-users" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to theano-users+unsubscr...@googlegroups.com. > For more options, visit https://groups.google.com/d/optout. > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
