JupyterNotebook

This article is a draft

This is not a complete article: This is a draft, a work in progress that is intended to be published into an article, which may or may not be ready for inclusion in the main wiki. It should not necessarily be considered factual or authoritative.

Graham cluster

Jupyter notebook comes in one Python model on Graham. You can get it working on the login node (not recommendable), and the compute nodes (highly recommendable). Note that any notebook running on the login node will be killed after sometime. You will have to submit a job requesting the # of CPU (or even GPU), amount of memory and runtime. Here, we give the instructions to submit a Jupyter job.

Load the module

Log onto graham.sharcnet.ca (or graham.computecanada.ca) and load the python module

ssh user@graham.sharcnet.ca
module load python35-scipy-stack

Install Python modules

pip3.5 install pycuda --user

Submit the job

Create a bash script for submitting a jupyter job on the slurm scheduler, i.e., slurm_jupyter.sh and add

#!/bin/bash
#SBATCH --gres=gpu:2 #only if you need GPU
#SBATCH --time=0-01:00 #runtime d-hh:mm
#SBATCH --nodes 1 #how many nodes
#SBATCH --ntasks-per-node 32 #number of cores per node
#SBATCH --mem-per-cpu 4000 # memory in MB
#SBATCH --job-name tunnel #name of the job
#SBATCH --output jupyter-log-%J.txt #name of the log file
#SBATCH --mail-type=BEGIN #send email if job has started
#SBATCH --mail-user=<email_address> #send the email to this email_address

## load modules that you might need, in this case cuda for pycuda

module load cuda 

## get tunneling info
XDG_RUNTIME_DIR=""
ipnport=$(shuf -i8000-9999 -n1)
ipnip=$(hostname -i | xargs)

## print tunneling instructions to jupyter-log-{jobid}.txt
echo -e "
        Copy/Paste this in your local terminal to ssh tunnel with remote
        -----------------------------------------------------------------
        sshuttle -r $USER@graham.sharcnet.ca -v $ipnip/24
        -----------------------------------------------------------------

        Then open a browser on your local machine to the following address
        ------------------------------------------------------------------
        http://$ipnip:$ipnport (prefix w/ https:// if using password)
        ------------------------------------------------------------------
        "
## start an ipcluster instance and launch jupyter server
jupyter-notebook --no-browser --port=$ipnport --ip=$ipnip

Making the tunneling

Open a new terminal window, and run the sshuttle command to port-forward the jupyter port, e.g.

 sshuttle -r jnandez@graham.sharcnet.ca -v 10.29.76.66/24

Opening in a browser

Open your local browser and type, e.g.

http://10.29.76.66:8850/