Open AlexPeng19 opened 6 years ago
Generally speaking, a single GPU is dozens of times faster than CPU. So I am afraid it will take months for you to train this model using CPUs.
@tramphero could i ask another question, while i am running librispeech/s5/run.sh. there is message as followings:
"This script is intended to be used with GPUs but you have not compiled Kaldi with CUDA If you want to use GPUs (and have them), go to src/, and configure and make on a machine where "nvcc" is installed."
after the command: steps/align_fmllr.sh --nj 30 --cmd "$train_cmd" \ 240 data/train_clean_100 data/lang exp/tri4b exp/tri4b_ali_clean_100
and it exit without any errors each time, does it mean i need to make some change on somewhere? looking forward your answer.
@tramphero i see, i checked local/nnet2/run_5a_clean_100.sh, i reset use_gpu=false, now it moved on.
i used the gridengine parallelism configuration with 24 thread to run, any possibility to shorten the period. i intended to run with multiple nodes, but it has error to find master node path, so i have to disable other nodes. did you ever come across this kind of problem?
@tramphero
This script is intended to be used with GPUs but you have not compiled Kaldi with CUDA If you want to use GPUs (and have them), go to src/, and configure and make on a machine where "nvcc" is installed.
i see the warning, maybe it will not block the trainning, but could i know how to shorten the training period if there is no gpu. i think my machine is well configured, it has 256G memory and 26 processor, but after two weeks training, it only complet half of the run.sh script. anybody could provide help?