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Pleiades singularity
Instructions last successfully run on May 29th 2025
Login
Login to PFE (Pleiades Front End).
Download image
Download this image in your scratch, as it might be large in size. This download needs to be done on the login node, as the interactive nodes can't seem to access the internet.
module load singularity singularity pull notebook_pangeo.sif docker://pangeo/pangeo-notebook~~ ~~
Update 05/29/2025: squashfs is banned on Pleiades, so I suggest trying this instead:
Get interactive node
(or something like that)
Run script
request_interactive_node.sh
, which has following content.run singularity
Run the following command or run a script with the following lines:
NB New users need to use
ls -l /nobackup/your_username
to identify which volume their nobackup direct is actually located in and bind to that directory.Run the script for using the CLI to access LLC data.
Use this: https://github.com/ocean-transport/pleiades_llc_recipes/blob/master/python_cli_data_export/extract_llc.py
Old access example
From: https://github.com/rabernat/pleiades_llc_recipes/blob/master/notebooks/pleiades_llc_examples.ipynb
Jupyter Lab
Following steps describe accessing a Jupyter lab session running in a singularity container via a browser running on your local machine (Mac, Linux, etc).
Secure Setup of Jupyter Notebook:
SSH into
pfe
and follow the steps in the article Secure Setup for Using Jupyter Notebook on NAS Systems to setup your password for Jupyter Lab.From
pfe
, SSH into an interactive node and run SingularityStart Jupyter Lab in the Singularity container. In the output below,
r403i7n4
is the interactive node we had gotten andsraza2
is a username. You would need to replace both of these in the next step. The output is attached here for reference purposes.Update the following items in the command below and run it in the terminal of your local machine (e.g., iTerm in Mac).
r403i7n4
with the name of the interactive node you getsraza2
with your NAS usernamepfe21
with the pfe node you log intoThis will create a SSH tunnel from your local machine port 8080 to port 8888 on
r403i7n4
Visit https://localhost:8080 in the browser on your local machine and enter Jupyter password you created in Step 1, when prompted.