Lawrence Livermore National Laboratory
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.

 

Press

Magma supercomputer

Cooling Magma is a challenge that Lawrence Livermore can take on

Thursday, June 4, 2020
LLNL's latest HPC system, aptly nicknamed “Magma," delivers 5.4 petaflops of peak performance crammed into 760 compute nodes.
Source: The Next Platform
series of images depicting the progression of a patient (current state) diagnosed with COVID-19

Lab team studies calibrated AI and DL models to more reliably diagnose and treat disease

Friday, May 29, 2020
A team led by an LLNL computer scientist proposes a deep learning approach aimed at improving the reliability of classifier models for predicting disease types from diagnostic images.
Source: LLNL News
topological analysis of X-ray CT data for recognition and trending of changes in microstructure under material aging

AI identifies change in microstructure in aging materials

Tuesday, May 26, 2020
LLNL scientists have taken a step forward in the design of future materials with improved performance by analyzing its microstructure using artificial intelligence.
Source: LLNL News
protein structures of SARS-CoV-2

COVID-19 research goes public through new portal

Tuesday, May 19, 2020
To help accelerate discovery of therapeutic antibodies or antiviral drugs for SARS-CoV-2, LLNL has launched a searchable data portal to share its COVID-19 research with scientists and the public.
Source: LLNL News
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.
Source: Data Skeptic
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.
Source: Better Scientific Software
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.
Source: LLNL News
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."
Source: insideHPC
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.
Source: Data Science Institute
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.
Source: LLNL News

Pages