HPSS
Livermore’s archive leverages a hierarchical storage management application that runs on a cluster architecture that is user-friendly, extremely scalable, and lightning fast.
Automated Testing System
LLNL’s Python 3–based ATS tool provides scientific code teams with automated regression testing across HPC architectures.
RADIUSS
The RADIUSS project aims to lower cost and improve agility by encouraging adoption of our core open-source software products for use in institutional applications.
Vanessa Sochat
Computer scientist Vanessa Sochat isn’t afraid to meet new experiences head on. With a Stanford PhD and a jump-right-in attitude, she joined LLNL to work on the BUILD project, Spack package…
Stephanie Brink
Computing relies on engineers like Stephanie Brink to keep the legacy codes running smoothly. “You’re only as fast as your slowest processor or your slowest function,” says Brink, who works in…
Ramesh Pankajakshan
Computational Scientist Ramesh Pankajakshan came to LLNL in 2016 directly from the University of Tennessee at Chattanooga. But unlike most recent hires from universities, he switched from research…
ISCP projects make machine learning advantages tangible
To keep employees abreast of the latest tools, two data science–focused projects are under way as part of Lawrence Livermore’s Institutional Scientific Capability Portfolio.
CASC Newsletter | Vol 14 | June 2024
This issue highlights some of CASC’s contributions to the DOE's Exascale Computing Project.
LLNL and BridgeBio announce trials for supercomputing-discovered cancer drug
In a milestone for supercomputing-aided drug design, LLNL and BridgeBio Oncology Therapeutics today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer.