Continuously monitor GPU usage

 For nvidia GPUs do the follwing:

nvidia-smi -l 1

Remote connection to a Jupyter notebook

 This is explained here

https://docs.anaconda.com/anaconda/user-guide/tasks/remote-jupyter-notebook/

Follow the following steps to use Jupyter Notebook launched from remote server.

Launch Jupyter Notebook from remote server, selecting a port number for <PORT>:

# Replace <PORT> with your selected port number

jupyter notebook --no-browser --port=<PORT>

For example, if you want to use port number 8080, you would run the following:

jupyter notebook --no-browser --port=8080

Or run the following command to launch with default port:

jupyter notebook --no-browser

Please note the port setting. You will need it in the next step.

You can access the notebook from your remote machine over SSH by setting up a SSH tunnel. Run the following command from your local machine:

# Replace <PORT> with the port number you selected in the above step

# Replace <REMOTE_USER> with the remote server username

# Replace <REMOTE_HOST> with your remote server address

ssh -L 8080:localhost:<PORT> <REMOTE_USER>@<REMOTE_HOST>

The above command opens up a new SSH session in the terminal.

Open a browser from your local machine and navigate to http://localhost:8080/, the Jupyter Notebook web interface. Replace 8080 with your port number used in step 1.

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If you want to use jupyter lab instead of notebook and connect remotely from visual studio you can follow these steps.

1. First start a jupyter lab server on the remote server:

jupyter lab --no-browser --NotebookApp.allow_origin='*' --port=8080

2. Now from visual studio connect to this server using the Jupyter extension

https://stackoverflow.com/questions/72121390/how-to-use-jupyterlab-in-visual-studio-code

you might have to install the extension first.