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The RStudio App in ARE allows you to start a dedicated RStudio instance on a Gadi compute node.

Starting a Session

  1. Login to ARE:
  2. Click the RStudio icon on the Dashboard (home page)

  3. Choose:
    1. the number of hours you want your session to run for (maximum)
    2. the compute queue you want to submit the job to
    3. the size of the compute resources you have access to (maximum).  If you attempt to exceed the CPU limit your processes will be throttled to the amount requested.  If you exceed the memory your Jupyter Kernel may be terminated.  Note: this is the resources used within the notebook; if you offload the processing to other jobs (e.g. using Dask) then you may not need a very large JupyterLab session
    4. select which project to allocate the SU from (must be a project with a current allocation, or the session will not start)
    5. select what storage (gdata and scratch areas) are required for your job to run
    6. select additional software licenses if required for your job
    7. if you want to receive an email once your session has started.  This is useful when the cluster is busy and your session is queued waiting for a free slot

  4. Optionally use the advanced options to specify additional environment variables or PBS directives for your session:

  5. Choose:
    1. Additional environment variables needed for your job
    2. jobfs size allocated to your job
    3. Additional PBS flags not covered by other options

  6. Click Launch button

  7. Initially it will show the status as Queued until your session begins to start. Once it is finished it will change to Running and look like the figure below

  8. Click the Connect to RStudio Server button
  9. This will open a new tab in your web browser that shows the RStudio session. NOTE: it can take a minute or two for the RStudio browser session to start
  10. If you close the window the session will remain running. To end the session you can  delete the job on the Interactive Sessions page of ARE

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