Groundbreaking accomplishments and national awards
LLNL Computation executives receive an award at SC18

Media Inquiries

If you have a general media-related question or comment or if you would like to arrange an interview, contact Jeremy Thomas, press officer, at (925) 422-5539 or via email.
News & Press

We make the news and break the records

LLNL Computing’s groundbreaking research and development activities, innovative technologies, and world-class staff are often featured in various media outlets. For more information on computing at LLNL, please explore the resources below.



screen shot of data skeptic podcast leaderboard

Podcast: Interpretable AI in Healthcare

Sunday, May 17, 2020
LLNL's Jay Thiagarajan joins the Data Skeptic podcast to discuss his recent paper "Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models." The episode runs 35:50.
people video chatting with an image of a cursor arrow on a computer screen

Working Remotely: The Spack Team

Sunday, May 17, 2020
Elaine Raybourn interviews LLNL's Todd Gamblin about the Spack project's experience working remotely.
simulation showing a laser interacting simultaneously with the melt pool and a large “spatter” of metal powder particle

Lab Devises Plan to Reduce Defects in 3D Metal Printing

Monday, May 11, 2020
Combining computer simulations with ultra-high-speed X-ray imaging, LLNL researchers have discovered a way to reduce defects in parts built through a laser-based metal 3D-printing process.
screen shot of the slide deck showing ALE simulations

Video: Incorporation of Machine Learning into Scientific Simulations at LLNL

Tuesday, May 5, 2020
In this video from the Stanford HPC Conference, Katie Lewis presents "The Incorporation of Machine Learning into Scientific Simulations at Lawrence Livermore National Laboratory."
abstract design showing layers of materials and chemicals on a stylized background

Building Knowledge and Insights using Machine Learning of Scientific Articles

Tuesday, May 5, 2020
An LLNL team developed ML tools that extract and structure information from the text and figures of nanomaterials articles using NLP, image analysis, computer vision, and visualization techniques.
3D structure of an antibody candidate is shown alongside the protein of SARS-CoV-

LLNL’s New ML Platform Generates Novel COVID-19 Antibody Sequences for Experimental Testing

Friday, May 1, 2020
LLNL researchers have identified an initial set of therapeutic antibody sequences, designed in a few weeks using machine learning and supercomputing, aimed at binding and neutralizing SARS-CoV-2.
screen shot of Sound Cloud interface showing podcast audio track

Flexible Package Manager Automates the Deployment of Software on Supercomputers

Tuesday, April 28, 2020
The Exascale Computing Project's Let's Talk Exascale podcast has a new episode featuring LLNL's Todd Gamblin, who talks about the package manager Spack. Episode 67 runs 5:54 and includes a transcript.
Corona supercomputer

Upgrades for LLNL Supercomputer from AMD, Penguin Computing Aid COVID-19 Research

Tuesday, April 21, 2020
AMD will supply upgraded GPUs for the Corona supercomputing cluster, which will be used by scientists working on discovering potential antibodies and antiviral compounds for SARS-CoV-2.
Hidden in Plain Sight podcast logo

Podcast: Using Data to Build a Secure Future

Tuesday, April 21, 2020
On the Hidden in Plain Sight podcast, LLNL director Bill Goldstein explains how the Lab crunches data to shape the future.
Computing summer students class of 2019

LLNL Summer Student Program Update

Thursday, April 16, 2020
This summer, LLNL will offer a remote program allowing students to carry out research projects by telecommuting, if their original project can be modified for online work.