Ragav, so when GPU is 98% utilized, is the training faster than when it's 35% utilized? Have you timed it?
On Wed, Nov 9, 2016 at 4:09 PM, Ragav Venkatesan <[email protected] > wrote: > After investigating further I don't think this is a speed or slow issue. I > think the newer version of CUDA/cuDNN using the cuda backend is not using > the GPU fully. The older version (7.5/5103) of CUDA/cuDNN produce 98% GPU > util but the same code on the latest versions (8.0/5105) don't. The code by > the way is the lenet tutorial from theano, so its not some weird coding > error also. Using the libgpuarray backend, I am able to produce 98% util > even with CUDA/cuDNN (8/5105). > > On Wednesday, November 9, 2016 at 9:48:40 AM UTC-7, nouiz wrote: >> >> It could be that the new back-end (libgpuarray) is faster and more >> efficient in that cases. So just use that back-end :) >> >> The speed difference between both back-end isn't constant, but should be >> a little bit faster with the new back-end in average. >> >> We have found a few speed regression in the new back-end, but they where >> fixed. If you found one, just tell us and we'll fix it. But the probably is >> still low of having slowdown in the new back-end. >> >> We just merged one such fix with indexing. Make sure to update >> libgpuarray and recompile it if you want to be sure to have the fastest >> version. >> >> Fred >> >> On Tue, Nov 8, 2016 at 1:56 PM, Ragav Venkatesan <[email protected]> >> wrote: >> >>> Ok, here is a problem I'm getting and I am not sure how to solve this. >>> If I use the libgpuarray backend on the cnn_tutorial I am getting a 98% gpu >>> tutilization with cudnn 5105. If I use cuda backend, I am only getting >>> about 35% utilization. >>> Anyidea why this might be so ? >>> >>> On Monday, October 24, 2016 at 9:38:17 AM UTC-7, nouiz wrote: >>>> >>>> What errors do you have? Delete your Theano cache, just in case and be >>>> sure to use Theano dev version. The last release don't support it I think. >>>> >>>> Fred >>>> >>>> On Mon, Oct 24, 2016 at 12:33 PM, Michael Klachko <[email protected] >>>> > wrote: >>>> >>>>> Yes, it's supported, I'm using it right now (CUDA 8.0 on Ubuntu 14.04): >>>>> >>>>> >>> import theano >>>>> Using gpu device 0: TITAN X (Pascal) (CNMeM is enabled with initial >>>>> size: 30.0% of memory, cuDNN 5105) >>>>> >>> print theano.__version__ >>>>> 0.9.0dev3.dev-20fd30a38d34687e9d944140042762ca9fca6276 >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On Saturday, October 22, 2016 at 2:54:00 PM UTC-7, Ragav Venkatesan >>>>> wrote: >>>>>> >>>>>> I updated and I'm getting some weird errors. With Cuda backend, >>>>>> convolutions only run on CPU and with libgpuarray backend GPUs only run >>>>>> at >>>>>> about 35% util. >>>>>> >>>>>> >>>>>> -- >>>>> >>>>> --- >>>>> 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 [email protected]. >>>>> 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 [email protected]. >>> For more options, visit https://groups.google.com/d/optout. >>> >> >> -- > > --- > You received this message because you are subscribed to a topic in the > Google Groups "theano-users" group. > To unsubscribe from this topic, visit https://groups.google.com/d/ > topic/theano-users/bSTnP3yLorw/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > [email protected]. > 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 [email protected]. For more options, visit https://groups.google.com/d/optout.
