Date
  • Sep 27, 2022, 10:30 am11:30 am
  • Oct 4, 2022, 10:30 am11:30 am
  • Oct 11, 2022, 10:30 am11:30 am
  • Oct 18, 2022, 10:30 am11:30 am
  • Oct 25, 2022, 10:30 am11:30 am
  • Nov 1, 2022, 10:30 am11:30 am
  • Nov 8, 2022, 10:30 am11:30 am
  • Nov 15, 2022, 10:30 am11:30 am
  • Nov 22, 2022, 10:30 am11:30 am
  • Nov 29, 2022, 10:30 am11:30 am
  • Dec 6, 2022, 10:30 am11:30 am
  • Dec 13, 2022, 10:30 am11:30 am
  • Dec 20, 2022, 10:30 am11:30 am
  • Dec 27, 2022, 10:30 am11:30 am
  • Jan 3, 2023, 10:30 am11:30 am
  • Jan 10, 2023, 10:30 am11:30 am
  • Jan 17, 2023, 10:30 am11:30 am
  • Jan 24, 2023, 10:30 am11:30 am
  • Jan 31, 2023, 10:30 am11:30 am
  • Feb 7, 2023, 10:30 am11:30 am
  • Feb 14, 2023, 10:30 am11:30 am
  • Feb 21, 2023, 10:30 am11:30 am
  • Feb 28, 2023, 10:30 am11:30 am
  • Mar 7, 2023, 10:30 am11:30 am
  • Mar 14, 2023, 10:30 am11:30 am
  • Mar 21, 2023, 10:30 am11:30 am
  • Mar 28, 2023, 10:30 am11:30 am
  • Apr 4, 2023, 10:30 am11:30 am
  • Apr 11, 2023, 10:30 am11:30 am
  • Apr 18, 2023, 10:30 am11:30 am
  • Apr 25, 2023, 10:30 am11:30 am
  • May 2, 2023, 10:30 am11:30 am
  • May 9, 2023, 10:30 am11:30 am
  • May 16, 2023, 10:30 am11:30 am
  • May 23, 2023, 10:30 am11:30 am
  • May 30, 2023, 10:30 am11:30 am
  • Jun 6, 2023, 10:30 am11:30 am
  • Jun 13, 2023, 10:30 am11:30 am
  • Jun 20, 2023, 10:30 am11:30 am
  • Jun 27, 2023, 10:30 am11:30 am
  • Jul 4, 2023, 10:30 am11:30 am
  • Jul 11, 2023, 10:30 am11:30 am
  • Jul 18, 2023, 10:30 am11:30 am
  • Jul 25, 2023, 10:30 am11:30 am
  • Aug 1, 2023, 10:30 am11:30 am
  • Aug 8, 2023, 10:30 am11:30 am
  • Aug 15, 2023, 10:30 am11:30 am
  • Aug 22, 2023, 10:30 am11:30 am
  • Aug 29, 2023, 10:30 am11:30 am
  • Sep 5, 2023, 10:30 am11:30 am
  • Sep 12, 2023, 10:30 am11:30 am
  • Sep 19, 2023, 10:30 am11:30 am
  • Sep 26, 2023, 10:30 am11:30 am
  • Oct 3, 2023, 10:30 am11:30 am
  • Oct 10, 2023, 10:30 am11:30 am
  • Oct 17, 2023, 10:30 am11:30 am
  • Oct 24, 2023, 10:30 am11:30 am
  • Oct 31, 2023, 10:30 am11:30 am
  • Nov 7, 2023, 10:30 am11:30 am
  • Nov 14, 2023, 10:30 am11:30 am
  • Nov 21, 2023, 10:30 am11:30 am
  • Nov 28, 2023, 10:30 am11:30 am
  • Dec 5, 2023, 10:30 am11:30 am
  • Dec 12, 2023, 10:30 am11:30 am
  • Dec 19, 2023, 10:30 am11:30 am
  • Jan 9, 2024, 10:30 am11:30 am
  • Jan 16, 2024, 10:30 am11:30 am
  • Jan 23, 2024, 10:30 am11:30 am
  • Jan 30, 2024, 10:30 am11:30 am
  • Feb 6, 2024, 10:30 am11:30 am
  • Feb 20, 2024, 10:30 am11:30 am
  • Feb 27, 2024, 10:30 am11:30 am
  • Mar 5, 2024, 9:30 am11:30 am
  • Mar 12, 2024, 9:30 am11:30 am
  • Mar 19, 2024, 9:30 am11:30 am
  • Mar 26, 2024, 9:30 am11:30 am
  • Apr 2, 2024, 9:30 am11:30 am
  • Apr 9, 2024, 9:30 am11:30 am
  • Apr 16, 2024, 9:30 am11:30 am
  • Apr 23, 2024, 9:30 am11:30 am
  • Apr 30, 2024, 9:30 am11:30 am
  • May 7, 2024, 9:30 am11:30 am
  • May 14, 2024, 9:30 am11:30 am
  • May 21, 2024, 9:30 am11:30 am
  • May 28, 2024, 9:30 am11:30 am
  • Jun 4, 2024, 9:30 am11:30 am
  • Jun 11, 2024, 9:30 am11:30 am
  • Jun 18, 2024, 9:30 am11:30 am
  • Jun 25, 2024, 9:30 am11:30 am
  • Jul 2, 2024, 9:30 am11:30 am
  • Jul 9, 2024, 9:30 am11:30 am
  • Jul 16, 2024, 9:30 am11:30 am
  • Jul 23, 2024, 9:30 am11:30 am
  • Jul 30, 2024, 9:30 am11:30 am
  • Aug 6, 2024, 9:30 am11:30 am
  • Aug 13, 2024, 9:30 am11:30 am
  • Aug 20, 2024, 9:30 am11:30 am
  • Aug 27, 2024, 9:30 am11:30 am
  • Sep 3, 2024, 9:30 am11:30 am
  • Sep 10, 2024, 9:30 am11:30 am
  • Sep 17, 2024, 9:30 am11:30 am
  • Sep 24, 2024, 9:30 am11:30 am
  • Oct 1, 2024, 9:30 am11:30 am
  • Oct 8, 2024, 9:30 am11:30 am
  • Oct 15, 2024, 9:30 am11:30 am
  • Oct 22, 2024, 9:30 am11:30 am
  • Oct 29, 2024, 9:30 am11:30 am
  • Nov 5, 2024, 9:30 am11:30 am
  • Nov 12, 2024, 9:30 am11:30 am
  • Nov 19, 2024, 9:30 am11:30 am
  • Nov 26, 2024, 9:30 am11:30 am
  • Dec 3, 2024, 9:30 am11:30 am
  • Dec 10, 2024, 9:30 am11:30 am

Details

Event Description

Where are Help Sessions located?

We're normally in the Fine Visualization Laboratory (A15 Fine Hall)

No Help Sessions on University holidays.

NOTE: Temporary alternate locations, if there are any changes, will be posted here:

  • No changes at this time

What are Help Sessions?

Looking for some help getting started? Can’t get your code to run? This is an opportunity to meet with research computing staff for one-on-one help. Topics include, but are certainly not limited to:

  • Getting started on the HPC clusters
  • Getting started with Linux
  • Understanding and troubleshooting error messages
  • Installing and compiling software
  • Writing SLURM submission scripts
  • Data analysis and visualization
  • Transferring and storing data
  • Debugging
  • Improving performance
  • Programming strategies
  • ... and many more

Think of this as Research Computing's office hours - no appointment necessary. Unfortunately, we are not available to meet outside of these hours. If you have an issue and you are unable to attend a help session then please submit a ticket by emailing [email protected].

Please be aware that we have limited staff and that, depending on the number of people who show up to a help session, we may not be able to get to you. We operate on a first-come, first-serve basis, but there are usually more support team members available for the second hour of each Help Session.

If you have a technical issue we encourage you to follow the steps outlined on this page:

https://researchcomputing.princeton.edu/support

Read a short article about the help sessions.

Visualization Help

You can get help with visualization programs, techniques, and data formats. In particular, how to effectively display your data.

If you are working with large amounts of data on the Princeton High-Performance Computing environment, you can use the tigressdata server to run visualization software on the data.  See the FAQ article, "How do I use VNC on Tigressdata?" for more information.

OIT Tech Clinic

If your issue relates to your own computer or relates directly to the Windows operating system then we encourage you to visit the OIT Tech Clinic.

Data & Statistical Services (DSS)

All questions about writing Stata code should be directed to DSS. Research Computing can help with problems related to running Stata code on our clusters. For help on R with data analysis please see the DSS website. DSS offers online tutorials and training for performing data analysis with R as well as one-on-one appointments. Issues related to running R on the HPC clusters are best addressed at the weekly help sessions described on this page.