Need Help?
Our Listserv: Keep Up To Date With the ML Cloud
We strongly recommend all ML Cloud users subscribe to our listserv and follow the information on the User Management Portal for the ML Cloud system status. This is the best way to stay notified of maintenance schedules, system outages, and other general interest items.
How To Submit a Help-Desk Ticket
One task of the ML Cloud Team is providing a support environment for any researcher within the Tübingen AI Center & the ML Center of Excellence. Our goal is to help researchers understand and operate with the ML Cloud infrastucture.
The ML Cloud Team operates regular working hours (9:00-17:30) Monday through Friday, except for public holidays. You can submit a help-desk ticket at any time via support@mlcloud.uni-tuebingen.de.
When submitting a help-desk ticket, please help the ML Cloud Team resolve the issue quicker by following these best practices when submitting tickets.
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Check the User Guide first to see if the issue has been documented first. Use the search function to quickly locate a FAQ, tutorial or additional information that's already published. Documentation may have changed since the last time you have accessed the ML Cloud, and your question may be addressed already
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Describe your issue precisely and completely. Please include:
- your ML Cloud username.
- a description of what you did, what happened, and the intended behavior.
- if applicable, what ML Cloud nodes you were using.
- if the problem is with a Slurm job, please include the Job ID number and the Slurm submission commands.
- screenshots of error messages or your job log, if possible.
When needed, please include additional information the ML Cloud team would need to understand your workflow (the directory containing your build and/or job script, the container or environment used, etc.).
- Be patient and considerate. Some dialogue may be needed before you and the ML Cloud Team are on the same page about an issue. If the admins disable your account or cancel your job, it's not punitive - when cluster-wide operations are endangered, or many users may be affected (e.g. the file system is in danger of crashing or a login node hangs), immediate action may be required without first notifying relevant users.
The ML Cloud Team
Kristina Kapanova (Head of the ML Cloud) kristina.kapanova(at)uni-tuebingen.de
Robert Pennington (System Administrator) robert.pennington(at)uni-tuebingen.de
Keroles Khalil (System Administrator) keroles.khalil(at)uni-tuebingen.de
Consultation
If you want to schedule a consultation with the team or discuss a relevant topic for your worklow on the ML Cloud, please use the contact scheduler:
Created: September 9, 2024