HMS - RStudio on O2
This app will start the RStudio application on one of the O2 cluster compute node. This application allows you to write R code, run it, and create graphs interactively.
Description of the available fields for customizing the O2 Portal job
Slurm Account:
Drop-down menu with your Slurm Account(s) - usually related to your lab name.
Partition:
The O2 partition you wish to submit the job to. You can use most partitions except "interactive". We recommend using the partition "priority".
Number of cores:
The number of CPU cores you want to allocate for this job.
Wall Time requested in hours:
This is the desired time, in hours, you want to allocate for the job. The maximum value admissible depends on the partition you selected.
Total Memory in GB:
This is the amount of memory (RAM) in GB you want to allocate for your job.
Modules to be loaded:
Enter the O2 modules to be loaded, typically gcc and R. Default is gcc/9.2.0 R/4.1.2
GPUs (optional):
If you selected a GPU partition, then specify the GPUs to allocate for the RStudio job.
GPU card type (optional):
If you selected a GPU partition, then select a GPU card type
Receive an Email
A checkbox to receive an email when the session starts
Show advanced settings
A checkbox to bring up a set of advance options
Optional Environment Setup
You can add additional commands here that will be executed before the RStudio server is started. This is an optional field and might not be necessary for most users.
Slurm Custom Arguments
This is an optional text field that can be used to pass additional flags to the Slurm scheduler when submitting the job.
Shared R Personal Library
Enter a path to a shared R Personal Library, which overwrites the ~/.Renviron file configuration.
For more information about the different jobs submission flags please read our main O2 wiki page at https://wiki.rc.hms.harvard.edu/display/O2.
After setting the above fields click on the Launch button which will submit the job.
While your job is pending on the queue you should see a page like:
The Session ID highlighted link can be used to see the log files created for the current jobs on a new OOD browser tab. Alternatively, you can click on the output.log hyperlink within the Progress & Error log section.
When the job is dispatched and ready to run you should see a screen like:
To open the RStudio application click on the Connect to RStudio Server button.
A new tab should open with the RStudio interface like:
Note - Modules are not available within the RStudio terminal
After you finish using the app, you need to close the RStudio browser tab and click on Delete from within the Open OnDemand Interactive session.
Note: Closing the browser will not terminate the active application. The OOD job will keep running until it reaches the requested Wall Time limit or the "Delete" button is used.
How to debug problems
If something does not work properly please make sure to record the actual O2 jobid printed at the top of the interactive app window
(33226137 in this example) and click on the ouput.log hyperlink (circled in red):
Once you click there, a new tab opens with information about the RStudio session. For example:
Often the reason of why a job failing is capture near or at the end of the output.log file.
If you need additional help you can reach out to rchelp@hms.harvard.edu, make sure to include the full path listed on the OOD file page along with any content printed in the output.log file.