Introduction to high performance computing with Savio training registration
Introduction to High Performance Computing with Savio training  
Monday, October 12 2020, 3:40-5pm
via Zoom (we will send the Zoom info after you register)

Research IT is offering an introductory training session on using Savio, the campus Linux high-performance computing cluster. We will give an overview of how the cluster is set up, different ways you can get access to the cluster, logging in, transferring files, accessing software on the system, and submitting and monitoring jobs. New, prospective, and current users of Savio and other campus high performance computing (HPC) clusters (Cortex and Vector) are invited.

There are no prerequisites, but it will be helpful to have a Savio account that you are able to log in to and to have a little bit of familiarity with using a UNIX-style command line (e.g., the Terminal on a Mac, or using the Linux command line).

If you'd like a basic tutorial on using the command line, please see: https://github.com/berkeley-scf/tutorial-unix-basics or https://swcarpentry.github.io/shell-novice 

For more details on getting a Savio account, please see: http://research-it.berkeley.edu/services/high-performance-computing/getting-account.

For those of you who would like hands-on assistance with the command line, including logging into Savio and using the command line on Savio, we will have several consultants available to help users get setup and answer basic questions, starting at 3pm.

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Name *
Email (@berkeley.edu preferred) *
Affiliation *
Please provide your Berkeley department, or if not affiliated with Berkeley, the organization you are associated with.
Position *
How much have you used Savio? *
Please indicate your level of interest in the following topics for the workshop. *
1: Not interested
2
3: Medium interest
4
5: Very interested
System description: hardware and disk space
Logging in and authentication
Data transfer and job input/output
Accessing software
Submitting and monitoring jobs
Using standard software (see next lines for specific tools)
Python
R
C/C++
MATLAB
Please list any other topics you would like to see covered
(If you have an interest in specific software not listed in the previous question, please mention it here.)
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