I'm trying to run the Deep Learning demo notebook, and it's taking a really long time on the training. It also doesn't look like it's using the GPU. I'm on an Amazon EC2 g2.2xlarge with the NVIDIA Corporation GK104GL [GRID K520](rev a1). I tried some of the solutions here: karpathy/char-rnn#89, like
require 'cunn'
require 'cutorch'
and th -l cutorch and th -l cunn from the command line. However, when I run the line
it just seems to sit there in progress and doesn't go anywhere. I also checked the GPU usage with nvidia-smi, and it looks like this:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 361.77 Driver Version: 361.77 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GRID K520 Off | 0000:00:03.0 Off | N/A |
| N/A 31C P8 26W / 125W | 121MiB / 4036MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 7379 C /home/ubuntu/torch/install/bin/luajit 119MiB |
+-----------------------------------------------------------------------------+
It jumps up in memory usage and starts the PID after require cutorch, and the memory usage never increases after that. GPU-Util sits at 0%. I have CUDA installed; nvcc --version gives:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Wed_May__4_21:01:56_CDT_2016
Cuda compilation tools, release 8.0, V8.0.26
It's running on Ubuntu 16.04. I verified the samples are working, and CUDA isn't giving any errors.
Any ideas why it wouldn't be using the GPU?
I'm trying to run the Deep Learning demo notebook, and it's taking a really long time on the training. It also doesn't look like it's using the GPU. I'm on an Amazon EC2 g2.2xlarge with the NVIDIA Corporation GK104GL [GRID K520](rev a1). I tried some of the solutions here: karpathy/char-rnn#89, like
and
th -l cutorchandth -l cunnfrom the command line. However, when I run the lineit just seems to sit there in progress and doesn't go anywhere. I also checked the GPU usage with nvidia-smi, and it looks like this:
It jumps up in memory usage and starts the PID after
require cutorch, and the memory usage never increases after that. GPU-Util sits at 0%. I have CUDA installed;nvcc --versiongives:It's running on Ubuntu 16.04. I verified the samples are working, and CUDA isn't giving any errors.
Any ideas why it wouldn't be using the GPU?