(under development)
Introduction
Jupyter Notebook is the original web application for creating and sharing computational document. It offers a simple, streamlined, document-centric experience. Jupyter Notebook is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media.
Usage
To be fleshed out
docker
Do Not Run Jupyter on the Login Nodes
The login or head node of each cluster is a resource that is shared by many users. Running Jupyter on one of these nodes may adversely affect other users. Please use one of the approaches described on this page to carry out your work.
Internet is Not Available on Compute Nodes, Only on OnDemand compute Nodes (currently n059). Jupyter sessions run on the compute nodes which do not have Internet access. This means that you will not be able to download files, clone a repo from GitHub, install packages, etc. You will need to perform these operations on the login node before starting the session. You can run commands which need Internet access on the login nodes (gc-prd-hpclogin1). Any files that you download while on the login node will be available on the OnDemand compute nodes. Internet access is available when running Jupyter on a OnDemand node. There is no job scheduler on the visualization nodes. Be sure to use these nodes in a way that is to fair all users.
Installation
Using Conda Environments: create a Conda environment on the login node
source /usr/local/bin/s3proxy.sh #To gain internet access on the login node
module load anaconda3/2021.11
conda create --name tf-cpu ipykernel tensorflow pandas matplotlib
exit
The ipykernel package should be installed
Reference
1. https://jupyter.org/try
2. https://researchcomputing.princeton.edu/support/knowledge-base/jupyter