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An interactive session is , in research cluster parlance, a scheduler job where you are free to enter run commands the same as if you logged into the server via SSHcan run commands in real-time (i.e., it is qualitatively identical a remote session started via Secure Shell or a terminal session that you've started on your laptop). If you're developing code in the cluster environment , want to check your code, or just run some commands on a cluster node or your analysis workflow isn't well-defined and you need to experiment with different command line tools then this is the option you want.The job will stay open similar to an ssh session, that is if you disconnect the session the job is over. This limitation can be circumvented through the use of programs such as screen or tmux

To run a simple an interactive job on the cluster use , invoke the srun command as shown below.on the login node (axon.rc) as demonstrated below:

srun --pty bash -i

Running the above command on the login node This command would start an interactive job with the default limits. After running this you You would then be running from one of the three gpu be provided with a session on one of Axon's nodes with one CPU core (and no GPU) allocation for a length of five daysfor the default job time limit (see here; currently 10 days as of 3/21).

srun --pty -c 2 --nodelist=ax08 --gres=gpu:gtx1080:2 -t 0-01:00 /bin/bash

In the command above the parameters are a as follows:

--pty says to start a pseudo terminal interactive session (mandatory for interactive sessions).

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/bin/bash is to run the program you wish to start in the interactive session, the bash shell (mandatory, you need to specify a program it doesn't have to be a command line interpreter like bash it could by python or matlab if that's what you want to run)

Running Jupyter Notebook Sessions on Axon

Axon has a command (sjupyter) that will start up a Jupyter notebook server automatically and give you the URL to connect. To use this command, first connect to the login node (e.g. ssh axon.rc.zi.columbia.edu), then navigate to the directory you want to start your notebook in, and finally run sjupyter.  For instance, if you wanted to run a Jupyter notebook within a directory named my-great-analysis that existed within your home directory, you might run the following commands:

jsp2205@Johns-MacBook-Pro [12:01:49]> ssh axon.rc.zi.columbia.edu
(base) [jsp2205@axon ~]$ cd ~/my-great-analysis
(base) [jsp2205@axon my-great-analysis]$ sjupyter
Waiting for the Jupyter Notebook SLURM job to start...
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Jupyter Notebook is starting...
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Jupyter Notebook has started
    To access the notebook, open this file in a browser:
        file:///home/jsp2205/.local/share/jupyter/runtime/nbserver-86057-open.html
    Or copy and paste one of these URLs:
        http://10.198.24.59:8614/?token=9c53efc98ab7757cb102b875bfee4c5da858f801ae90b906
To turn off Jupyter notebook, run "scancel 45737".
To reprint the URL for the Jupyter notebook, run "/usr/local/bin/sjupyter --get-notebook-url=45737".

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(base) [jsp2205@axon ~]$ sjupyter --get-notebook-url=45737
    To access the notebook, open this file in a browser:
        file:///home/jsp2205/.local/share/jupyter/runtime/nbserver-86057-open.html
    Or copy and paste one of these URLs:
        http://10.198.24.59:8614/?token=9c53efc98ab7757cb102b875bfee4c5da858f801ae90b906

To turn off a Jupyter notebook instance, you may use the standard SLURM job cancelling command (scancel).  Note that there is a time limit of 5 days for jobs that run on the shared or burst partitions (see Slurm Overview), so any Jupyter notebook servers running on these partitions will be cancelled automatically after the time limit is exceeded.

sjupyter can also be run with any of the standard sbatch flags, so if you want to specify exactly what resources should be available to the Jupyter notebook instance, you may do so by appending sbatch options to the command you run.  For instance, the command below requests that 3 GPUs and 16 GB of memory per CPU be available to the Jupyter notebook:

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