Using Conda Environments
Using Widgets
Requesting a GPU
Do Not Run Jupyter on the Login Nodes
Base Conda Environment
Custom Conda Environment
Another Approach
Running as a batch job
#!/bin/bash #PBS -m abe #PBS -M YourEmail@griffithuni.edu.au #PBS -N myJupyterJob ###If not using gpu,you should not request gpuq2. You can use workq or something similar #PBS -q gpuq2 ### Number of nodes:Number of CPUs:Number of threads per node. ###If not using gpu,you should not request ngpus #PBS -l select=1:ncpus=1:ngpus=1:mem=10gb,walltime=10:00:00 # The job's working directory cd $PBS_O_WORKDIR module load anaconda3/2021.11 #activate your env #source activate protein source /usr/local/bin/s3proxy.sh unset PYTHONPATH jupyter-lab --no-browser --port=8889 --ip=0.0.0.0
After running the above script and the job has started on the compute node, you run the following command on your local machine to start port forwarding.
For n060 gpu node
ssh -CNL 5678:localhost:5678 s123456@n060.rcs.griffith.edu.au
For node gpu node n061:
ssh -N -f -L 8889:n061:8889 -J s123456@gc-prd-hpclogin1.rcs.griffith.edu.au s123456@n061