I'm not sure, but just by looking at CPU usage (top command on Linux) you should be able to see the difference.
On Sat, Nov 12, 2016 at 6:19 PM, Ragav Venkatesan < [email protected]> wrote: > Both are using CUdNNs.. I am wondering if some ops are running on the CPU, > how do I find that out ? > > On Friday, November 11, 2016 at 10:00:39 PM UTC-7, Michael Klachko wrote: >> >> Do both versions use CuDNN? If gpu0 version didn't use it, that would >> explain the difference. Also, look at CPU usage for gpu0 version - it could >> be that some ops are running on CPU instead of GPU. >> >> On Fri, Nov 11, 2016 at 2:20 PM, Ragav Venkatesan <[email protected]> >> wrote: >> >>> Running on GTX 1080, cuda0 for device runs for 1.69 minutes at 98% , >>> gpu0 runs for 5.12 minutes at 34% . Both runs the same code cnn_tutorial >>> from theano tutorials. The code is not modified or changed at all. >>> floatX=float32, mode = FAST_RUN, nvcc.fastmath = True and nvcc.allowgc >>> =True. >>> >>> On Thursday, November 10, 2016 at 4:47:38 PM UTC-7, Michael Klachko >>> wrote: >>>> >>>> Yes. It depends on the size of your network/input - the smaller it is, >>>> the harder it is to keep 3k cores busy all the time. >>>> Regarding timing, you don't need to write much code: >>>> >>>> import time >>>> start_time = time.time() >>>> your code here >>>> print "Code ran for {:.1f} minutes".format((time.time() - >>>> start_time)/60) >>>> >>>> >>>> >>>> >>>> On Thu, Nov 10, 2016 at 3:26 PM, Ragav Venkatesan < >>>> [email protected]> wrote: >>>> >>>>> I'm writing a code to test this, but why do you ask this ? Is there a >>>>> case where nvidia-smi might give me 35% util when the GPU is actually >>>>> running the code as fast as it can ? >>>>> >>>>> On Wednesday, November 9, 2016 at 5:36:14 PM UTC-7, Michael Klachko >>>>> wrote: >>>>>> >>>>>> 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/to >>>>>>> pic/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 a topic in the >>>>> Google Groups "theano-users" group. >>>>> To unsubscribe from this topic, visit https://groups.google.com/d/to >>>>> pic/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 a topic in the >>> Google Groups "theano-users" group. >>> To unsubscribe from this topic, visit https://groups.google.com/d/to >>> pic/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 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. 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