Start Up Sequence
Your set up is complete. Here is the inventory of the items you prepared to execute this method to connect and run Jupyter Notebook from HYAK:
| Element | klone or local | Notes |
|---|---|---|
hyak-container.sif | klone | container image; directly or with a symbolic link |
conda-overlay.img | klone | container overlay with conda and jupyter environment; in read-write or read-only mode |
launch-container.sh | klone | launches container and overlay; in read-write or read-only mode |
start-jupyter-server.sh | klone | starts jupyter |
jupyter-server.job | klone | sbatch script that launches the container-overlay and jupyter as a SLURM job |
~/.ssh/config | local | creates ssh klone-login short cut |
~/.ssh/klone-node-config | local | creates ssh klone-node short cut for ProxyJump |
set-hyak-node.sh | local | replaces Hostname in ~/.ssh/klone-node-config for convenience |
start-jupyter-forwarding.sh | local | starts port forwarding and provides web address for Jupyter Notebook |
important
Before we begin the Start Up Sequence, make sure that you have no jobs called klone-container running on klone.
If you do, you can cancel the job with scancel and the JobID:
Now we begin the Start Up Sequence:
1. Login to klone#
Log in using your klone-login short cut.
2. Navigate to your working directory#
Change directory to the directory you have been using during this tutorial, where you have your materials stored. For example:
3. Start the Jupyter SLURM job#
Submit the jupyter-server.job script with sbatch to start a job running the container-overlay and jupyter.
Use the watch command with the squeue command to monitor the job in real time. watch -n10 will issue the squeue every 10 seconds. Use Ctrl + C to exit the watch command.
Once the job is running, or you see R under the column ST using squeue, use Ctrl + C to exit the watch command.
In your working directory, you will have a file called jupyter-server-XXXXXX.out where the X's are the jobID assigned to the job by SLURM. Use the command tail --follow to print the contents of the jupyter-server-XXXXXX.out file and wait for the message, "Info: Jupyter server is running, port & token in ~/.jupyter-port-and-token." Once you see this message, your Jupyter server session is ready for the next step. (Use Ctrl + C to exit the tail command)
4. Prepare your ProxyJump to the compute node#
caution
The next steps are performed on your local computer.
Above we used squeue to monitor the job we started. The NODELIST column of the squeue output shows the node where the job is running. This is the Hostname for our ~/.ssh/klone-node-config script.
Let's try to execute the set-hyak-node.sh script and see if it will replace our Hostname with n3219 where the job is running (the compute node will likely be different for you; n3219 is just an example).
If it didn't work, please use a text editor to manually change Hostname to the node where your job is running.
5. Start Port Forwarding#
caution
The next steps are performed on your local computer.
Execute the start-jupyter-forwarding.sh script to get the web address to use Jupyter Notebook in the browser.
Copy and paste the web address into your browser, and you should be connected to your Jupyter server where you can work in a Jupyter Notebook.
When you're finished, you can use the kill command we generated to ensure your port forwarding is stopped: