From: Jan T. <jt...@gm...> - 2015-07-15 16:04:07
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Are you sure you are using CUDA? You have to enable the support manually when running the kaldi configure script. As you have gaming cards, nvidia-smi won't probably display GPU utilization. You can have a look at the temperature of the cards to verify the GPUs are used. Expect ~ 4 times longer time for the ensemble training than for the "normal" training. y. On Wed, Jul 15, 2015 at 5:10 AM, Cemil Demir <cem...@gm...> wrote: > Hi, > > I have a workstation which have 4 NVIDIA TITAN X GPU card. > > I want to train a DNN model using egs/babel/s5c recipe. I am using > "run-2a-nnet-ensemble-gpu.sh" script. > > When I use "run-2a-nnet-gpu.sh" script, the accuracy is below as compared > to sgmm-mmi case. Therefore I > > Total amount of training data is 13 hours. > want to use "ensemble" version. > > Training takes about 35 hours. I think, it is too slow. > > Could give me any suggestion to speed up training? > > İt is a little bit urgent for me. > > Thank you. > > -- > Cemil Demir > > cem...@gm... > > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > _______________________________________________ > Kaldi-developers mailing list > Kal...@li... > https://lists.sourceforge.net/lists/listinfo/kaldi-developers > > |