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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
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docker
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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. Jupyter sessions will have to 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 compute nodes.
Installation
Using Conda Environments: create a Conda environment on the login node
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conda create --name widg-env --channel conda-forge matplotlib jupyterlab ipywidgets ipympl
Usage
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. Jupyter sessions will have to 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 compute nodes.
# from behind VPN if off-campus or on wireless ssh snumber@n059,rcs,griffith.edu.au module load anaconda3/2020.11
source activate snumber-tf-cpu #e.g source activate s123456-tf-cpu jupyter-notebook --no-browser --port=8889 --ip=127.0.0.1 # note the last line of the output which will be something like http://127.0.0.1:8889/?token=61f8a2aa8ad5e469d14d6a1f59baac05a8d9577916bd7eb0 # leave the session running
Then in a new terminal on your laptop,
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