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# from behind VPN if off-campus or on wireless ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au module load anaconda3/2021.11 source activate <you environment> #e.g source activate s123456-tf-cpu conda install <another-package-1> <another-package-2> #To see the packages in your Conda environment, run this command conda list conda deactivate exit For some packages you will need to add the conda-forge channel or even perform the installation using pip as the last step. |
Using Custom Conda Environment
The procedure above will only be useful if you only need the base Conda environment which includes just less than three hundred packages. If you need custom packages then you should create a new Conda environment and include jupyter in addition to the other packages that you need. The necessary modifications are shown below:
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# from behind VPN if off-campus or on wireless
ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au
ssh snumber@@gc-prd-hpclogin1.rcs.griffith.edu.au
module load anaconda3/2020.11
source /usr/local/bin/s3proxy.sh
conda create --name myenv jupyter <package-2> <package-3>
source activate myenv
#To see the packages in your Conda environment, run this command
conda list
conda deactivate
exit
|
The packages in the base environment will not be available in your custom environment unless you explicitly list them (e.g., numpy, matplotlib, scipy).
Using Widgets
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# from behind VPN if off-campus or on wireless ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au source /usr/local/bin/s3proxy.sh #To gain internet access on the login node module load anaconda3/2021.11 conda create --name widg-env --channel conda-forge matplotlib jupyterlab ipywidgets ipympl source activate widg-env #To see the packages in your Conda environment, run this command conda list conda deactivate exit |
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 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 on the compute nodes. You will need to perform these operations on the login node node (e.g gc-prd-hpclogin1.rcs.griffith.edu.au) 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.
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ssh -N -f -L localhost:8889:localhost:8889 snumber@n059.rcs.griffith.edu.au |
Custom Conda Environment
The procedure above will only be useful if you only need the base Conda environment which includes just less than three hundred packages. If you need custom packages then you should create a new Conda environment and include jupyter in addition to the other packages that you need. The necessary modifications are shown below:
| No Format |
|---|
# from behind VPN if off-campus or on wireless
ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au
module load anaconda3/2020.11
source /usr/local/bin/s3proxy.sh
conda create --name myenv jupyter <package-2> <package-3>
source activate myenv
#To see the packages in your Conda environment, run this command
conda list
conda deactivate
exit |
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.rcs.griffith.edu.au |
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Running on a Compute Node via interative pbs
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netstat -antp | grep :88 | sort
onDemand Nodes
Internet access is available when running Jupyter on a OnDemand node (n059,rcs,griffith.edu.au). There is no job scheduler on the onDemand nodes. Be sure to use these nodes in a way that is to fair all users.
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# 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 |
# from behind VPN if off-campus or on wireless
ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au module load anaconda3/2020.11
jupyter-notebook --no-browser --port=8889 --ip=127.0.0.1
The packages in the base environment will not be available in your custom environment unless you explicitly list them (e.g., numpy, matplotlib, scipy).
Then in a new terminal on your laptop,
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