The award winners include a software suite that helps apply deep learning techniques to science and data challenges in cancer research; software that helps better understand the power, energy and performance of supercomputers; and a number format that permits fast, accurate data compression for modern supercomputer applications.
Livermore Lab Team Boosts Trust in AI for Science by Making Machine Learning Explainable
August 1, 2023 by
As machine learning techniques become increasingly used in the sciences, a team of researchers in Lawrence Livermore National Laboratory’s Computing and Physical and Life Sciences directorates are trying to provide a reasonable starting place for scientists who want to apply machine learning but lack a strong ML background. The goal is to help users understand […]
LLNL Director Kim Budil Named to Fast Company’s List of Most Creative People in Business
July 7, 2023 by
July 6, 2023 — Lawrence Livermore National Laboratory (LLNL) Director Kim Budil has been selected by Fast Company as one of the Most Creative People in Business for 2023. The annual list, in its 15th year, recognizes individuals making an impact in society via daring achievements in their chosen fields, from tech to design to healthcare. Budil was selected […]
El Capitan Supercomputer Installation at Livermore Has Begun
July 5, 2023 by
With pictures to prove it, Lawrence Livermore National Laboratory announced today it has begun receiving and installing components for El Capitan, what is expected to be the third exascale-class supercomputer in the U.S. The laboratory shared photos on social media today. Projected to exceed 2 exaflops, El Capitan will likely be the most powerful supercomputer […]
LLNL and Korea Institute of Science and Technology to collaborate
August 22, 2022 by
Livermore, CA — Leaders at Lawrence Livermore National Laboratory (LLNL) and the Korea Institute of Science and Technology (KIST) have signed a memorandum of understanding (MOU) to collaborate on basic science and technology in the renewable energy, climate science, data science and characterizations arenas. Under the MOU, KIST will have office space in the Livermore […]
NNSA Completes LLNL Exascale Facility for El Capitan
June 10, 2022 by
WASHINGTON – The Department of Energy’s National Nuclear Security Administration (NNSA) today announced the completion of construction on the Exascale Computing Facility Modernization project at the Lawrence Livermore National Laboratory in Livermore, California. The project upgraded the electrical and mechanical capabilities of the Livermore Computing Center, which will enable the facility to power the first […]
LLNL and Amazon Web Services Team on Standardized HPC Software Stack
May 26, 2022 by
Lawrence Livermore National Laboratory (LLNL) and Amazon Web Services (AWS) have signed a memorandum of understanding to define the role of leadership-class high performance computing (HPC) “in a future where cloud HPC is ubiquitous,” the two organizations said. LLNL and AWS said they will explore software and hardware solutions spanning cloud and on-premises HPC environments, with the […]
LLNL Entrepreneur Hall of Fame Inducts 1 Current, 2 Former Lab Scientists
March 29, 2022 by
One current and two former Lawrence Livermore National Laboratory (LLNL) scientists have been inducted into the Laboratory’s Entrepreneurs’ Hall of Fame (EHF). The trio, who represent the third class of inductees into the Lab’s EHF, have been honored for developing technologies during or after their lab careers that created major economic impacts or spawned new […]
LLNL Scientists Use Sierra Supercomputer to Develop Cancer Model
January 10, 2022 by
Jan. 10, 2022 — Lawrence Livermore National Laboratory researchers and a multi-institutional team of scientists have developed a highly detailed, machine learning-backed multiscale model revealing the importance of lipids to the signaling dynamics of RAS, a family of proteins whose mutations are linked to numerous cancers. The team simulated a one micron-by-one micron patch on […]
LLNL Team Wins SC21 Reproducibility Advancement Award for Approximation Framework
November 18, 2021 by
A suite developed by a Lawrence Livermore National Laboratory (LLNL) team to simplify evaluation of approximation techniques for scientific applications has won the first-ever Best Reproducibility Advancement Award at the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC21). Newly instituted by the conference, the award recognizes outstanding efforts in advancing transparency […]
