Research IT
provides research data and computing technologies, consulting, and community for the UC Berkeley campus. Our goal is to advance research through IT innovation.

Status and Service Updates
No office hours during Spring Break: 3/26-3/27
Research IT will not hold office hours during Spring Break on Wednesday, 3/26 and Thursday, 3/27. Please get in touch with us via e-mail in the meantime and we will be happy to assist you.
Data Center Shut Down and Savio Downtime: Fri, 3/28 (5pm) - Tues, 4/1 (8am)
Our campus data center will temporarily shut down on Sunday, March 30, for essential generator work. In conjunction with this work, the Savio cluster will also be offline, starting Friday, March 28, at 5 p.m. until Tuesday, April 1, at 8 a.m. Pacific. A scheduler reservation is in place to ensure no jobs run after 5:00 p.m. on March 28th. If you plan to submit jobs, please ask for proper wall time to complete them before the downtime. Otherwise, your jobs will wait in the queue until the cluster is back online.
Savio is back online: Thurs, 3/13
We have restored the Savio cluster and it is back online. However, your jobs might have failed due to an abrupt power down. Please check your jobs and resubmit or restart if you have checkpoint files. Once again thank you for your patience and understanding.
News Articles
An Interview with Jon Stiles and Rick Jaffe of the D-Lab’s Securing Research Data Working Group
The Securing Research Data working group, run by Jon Stiles of the D-Lab and Rick Jaffe of Research IT, provides a forum for
Workshops & demos for researchers: Reproducibility, Security, HPC, and Cloud. Feb 11-14 is Love Data Week!
Please join us for a series of events on February 11th-15th during Love Data Week.
This nationwide campaign is designed to raise awareness about
Improving campus services for working with sensitive data
Amy Neeser co-authored this post with Chris Hoffman
Increasingly, researchers in a wide range of fields at UC Berkeley are applying novel data science approaches to very large sensitive and restricted data sets. Working closely with
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