In this tutorial we will create a Python environment with PyTorch and see how to get Jupyterlab running on a GPU node.
First of all we want to create an isolated Python environment, I generally favor micromamba
, see the documentation on how to install it
Once installed, create an environment:
micromamba create -n pytorch python==3.10 jupyterlab
Do not install pytorch
with Mamba, it won’t recognize the GPU, not sure why.
Install pytorch
with pip
:
micromamba activate pytorch
pip install pytorch
The tool to launch JupyterLab on Expanse currently doesn’t support mamba, so the easiest way is to activate this environment at login, therefore add:
micromamba activate pytorch
at the end of .bashrc
.
Finally we can launch a job on the GPU-shared partition with Galyleo to get JupyterLab proxied to a public url:
/cm/shared/apps/sdsc/galyleo/galyleo.sh launch -Q -p gpu-shared -A sds166 -t 120 -c 8 -M 16 -G 1 -j lab
Check in a Notebook that pytorch
detects the GPU:
import torch
torch.cuda.is_available()