Content Comparison

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• Quick Links:
  • EDU pod virtual host: edupod.cns.utexas.edu
    • e.g. https://edupod.cns.utexas.edu for the RStudio and JupyterHub server web applications
    • the AMDG pod does not have a virtual host name
  • Understanding and troubleshooting the R Studio Server and JupyterHub web applications
    • About R and R Studio Server
      
    • About Python and JupyterHub server
  • BRCF support email: rctf-support@utexas.edu
  • EDU pod Course Management interface: 
    • https://rctf-account-request.icmb.utexas.edu/edu-pod/ 
      • accessible only from the UT campus network or with the UT VPN service active
    • AMDG pod course management is performed by BRCF staff
  • About the AMDG pod GPU-enabled software environment: AMD GPU servers
• Important Notes:
  • Each pod has common Home, Work and Scratch storage areas.
  • Account EIDs must be entered in lowercase when logging in, either by SSH or to the RStudio Server/JupyterHub web applications.
    • Please let your students know to enter their EIDs using all lowercase letters.
  • EDU and AMDG pod course accounts are deactivated a few weeks after each semester ends (see Data/account retention)
    
    • Please let your students know this so they can ensure any files they want to retain in their Home directories are transferred elsewhere.

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Both R Studio Server and JupyterHub web environments have a large number of packages available. Instructors can also request that additional software be installed. Such requests should ideally be made at least two weeks before the start of a course.

Note that long-running R and Python processes should generally be run from the command line rather than in the web applications, as duration of work there is limited by session timeouts (e.g. 120 minutes currently for R Studio Server).

See About R and R Studio Server for information about the R Studio Server web application and the command-line R environments, and how to troubleshoot common problems.

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• Post assignments to Canvas. Have students download to their personal computers, then Upload to their Home directory in RStudio Server or JupyterHub.

  • Note: There is a 64K file-size limit on uploading files in JupyterHub, so the RStudio Server upload function should be used instead for files larter than 64K.

  • When the assignment is complete, students can copy the files from their Home directory back to their personal computer using a remote file system transfer tool such as scp. This transfer must be initiated from the user's computer, as shown here. Then the completed assignment can be uploaded to Canvas from there.

  • Note: There is a 64 Megabyte file-size limit on uploading files in both JupyterHub and RStudio Server, so an alternate method should be used for files larger than 64M.

# From the student's personal computer
cd my_homework_directory
scp amb599@educcomp01.ccbb.utexas.edu:~/homework1.amb599.R . 

• Instructors can post assignments to their shared /stor/work/<Class_Semester> directory as describe in the Posting assignments to the shared course directory section.

  • After posting an assignment, instructors can have students copy it to their Home directory using a Terminal pane in RStudio Server, or JupyterHub, renaming it in the process. When finished, use a Terminal pane to copy the assignment to the shared /stor/work/<Course_Semester> directory.

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