Undergraduate student uses Savio to perform Natural Language Processing on Fanfiction

Smitha Milli and David Bamman

Smitha Milli, a fourth year Electrical Engineering and Computer Science (EECS) undergraduate student at UC Berkeley, is collaborating with David Bamman, Assistant Professor at the Berkeley School of Information, to perform Natural Language Processing (NLP) on fanfiction texts.

BRC program supports neutron transport research and advanced nuclear reactor design

Fission source distribution of a hexagonal array of UO2 pins in water calculated by WARP software.

To assess the stability and safety of proposed nuclear reactor designs, UC Berkeley nuclear engineers utilize the campus High Performance Computing (HPC) cluster, Savio, to predictively model the pathways of neutrons as they collide with atoms in the nuclear fuel. Kelly Rowland, a PhD student in Professor Rachel Slaybaugh’s lab, and a domain consultant with Berkeley Research Computing (BRC), develops and tests computational methods for simulating neutron motion.

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BRC Program receives NSF grant for Cyberinfrastructure Engineer

NSF site announcement of CI Engineer award to UC Berkeley

A Cyberinfrastructure Engineer funded by the National Science Foundation (NSF)  will soon begin to help researchers adapt and scale research workflows to take advantage of campus cyberinfrastructure including the Berkeley Research Computing (BRC) resources, the Science DMZ and associated high-speed networking, and high-speed data transfer tools. The position will be funded by an ACI Campus Cyberinfrastructure (CC-NIE) grant awarded by the NSF in December 2015, and will augment the BRC Program’s staff.

Savio cluster storage quadrupled to support Big Data research

The campus’ Savio computing cluster received a major storage upgrade on June 12, 2015, when its Global Scratch file system was quadrupled in size, to a massive 885 terabytes (TB) of storage. The upgraded storage is also 250% faster, providing a peak bandwidth of over 20 GB per second, to better meet the demands of data intensive computations.