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.



presentation slide showing a watercolor rabbit overlaid on a photo of a forest

Livermore’s El Capitan supercomputer to debut HPE ‘Rabbit’ near node local storage

Thursday, February 18, 2021
A near node local storage innovation called Rabbit factored heavily into LLNL’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan.
illustration showing the LbC method of simulator inputs into a prediction estimator

Lab researchers explore ‘learn-by-calibration’ approach to deep learning to accurately emulate scientific process

Wednesday, February 10, 2021
An LLNL team has developed a “Learn-by-Calibrating” method for creating powerful scientific emulators that could be used as proxies for far more computationally intensive simulators.
abstract graphic of a brain and network overlaid with the CASC logo

CASC research in machine learning robustness debuts at AAAI conference

Wednesday, February 10, 2021
Three papers address feature importance estimation under distribution shifts, attribute-guided adversarial training, and uncertainty matching in graph neural networks.
collage of Lab scenes with glassdoor logo

Lab makes Glassdoor’s 2021 list of ‘Best Places to Work’

Wednesday, January 13, 2021
For the third consecutive year, LLNL has been honored with a Glassdoor Employees’ Choice Award, recognizing the Best Places to Work in 2021.
successive photos of a cheetah with a patch of the image generated by a machine learning algorithm

Lawrence Livermore computer scientist heads award-winning computer vision research

Friday, January 8, 2021
A team led by LLNL developed a new kind of prior—a characterization of the space of natural images—for compressive image recovery that is trained on patches of images instead of full-sized images.
 simulation of protein-lipid dynamics for a 1 µm x 1 µm membrane subsection at near-atomistic resolution

Scientists tap the power of HPC in a bet to understand cancer growth

Wednesday, December 23, 2020
A multi-institutional team including LLNL is using Summit, America’s fastest supercomputer, to understand how certain proteins signal body cells to reproduce uncontrollably, triggering cancer.
Photo of Bronis next to IEEE logo

LLNL’s de Supinski earns prestigious IEEE Fellowship

Wednesday, December 9, 2020
IEEE, the world's largest technical professional organization, has named Livermore Computing CTO Bronis de Supinski to its 2021 Class of Fellows for his leadership in large-scale computing systems.
NeurIPS logo next to a diagram of a robust machine learning life cycle

NeurIPS papers aim to improve understanding and robustness of machine learning algorithms

Monday, December 7, 2020
The 34th Conference on Neural Information Processing Systems features two papers advancing the reliability of deep learning for mission-critical applications at LLNL.
GWC logo next to a screen shot of multiple people in video chat

Girls Who Code – ‘Big’ program goes virtual

Tuesday, November 24, 2020
The first-ever virtual Girls Who Code – "Big" program (a collaboration between LLNL, the Livermore Lab Foundation, and the Livermore Valley Joint Unified School District) recently wrapped up.
Blue Gene/L supercomputer

LLNL, IBM win SC20 ‘Test of Time’ for Blue Gene/L

Friday, November 20, 2020
A team of current and former LLNL and IBM scientists won the annual “Test of Time” award at the 2020 Supercomputing Conference on November 19 for a paper outlining LLNL’s Blue Gene/L supercomputer.