I will try testing it on Pascal Titan X card when I have time tomorrow, and will report back.
On Sat, Nov 12, 2016 at 9:36 PM, Ragav Venkatesan < [email protected]> wrote: > When I was debugging, I also discovered that if I use ignore_border = > False for pooling, it doesn't run on GPU in libgpuarray backend. > ignore_border = True does. Is there anything to this ? > > > On Saturday, November 12, 2016 at 7:45:22 PM UTC-7, Ragav Venkatesan wrote: >> >> in htop I usually have one CPU running 100% for both cases. >> >> >> On Saturday, November 12, 2016 at 7:43:16 PM UTC-7, Michael Klachko wrote: >>> >>> 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/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 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 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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