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LLNL welcomes 'Ruby' supercomputer for national nuclear security mission and COVID-19 research
Lawrence Livermore National Laboratory (LLNL), along with partners Intel, Supermicro and Cornelis Networks, have deployed “Ruby,” a high performance computing (HPC) cluster that will perform functions for the National Nuclear Security Administration (NNSA) and support the Laboratory’s COVID-19 research. Funded by NNSA’s Advanced Simulation and Computing (ASC) program, the…
LLNL, partners open access to CO2 storage simulator
After more than two years of joint research, Lawrence Livermore National Laboratory (LLNL), Total and Stanford University are releasing an open-source, high-performance simulator for large-scale geological carbon dioxide (CO2) storage. The GEOSX simulator will enable researchers around the world to build on the work of the three partners, providing an open framework to…
Department of Energy to showcase scientific computational expertise at SC20
The scientific computing and networking leadership of 17 Department of Energy (DOE) national laboratories will be showcased at SC20, the International Conference for High-Performance Computing, Networking, Storage and Analysis, taking place Nov. 9-19 for the first time via a completely virtual format. Like most conferences and workshops being held this year across the U.S…
Women’s math association names Woodward fellow
The Association for Women in Mathematics (AWM) announced it has named Lawrence Livermore National Laboratory (LLNL) computational scientist Carol Woodward as a 2021 fellow, recognizing her commitment to supporting and advancing women in the mathematical sciences. A computational mathematician in the Center for Applied Scientific Computing (CASC) since 1996, Woodward’s…
Lab explores new resins for light-based 3D printing
A Lawrence Livermore National Laboratory (LLNL) team has simulated the cross-linking of 3D-printed polymer networks, a key step toward developing new functional resins for light-based 3D-printing techniques including two-photon lithography (TPL) and volumetric additive manufacturing (VAM). The team used molecular dynamics simulations to study, at a microscopic level, the…
Mammoth computing cluster to aid COVID research
Lawrence Livermore National Laboratory (LLNL) and its partners AMD, Supermicro and Cornelis Networks have installed a new high performance computing (HPC) cluster with memory and data storage capabilities optimized for data-intensive COVID-19 research and pandemic response. Funded by the Coronavirus Aid, Relief and Economic Security (CARES) Act, the “big memory” cluster,…
AI gets a boost via LLNL, SambaNova collaboration
Lawrence Livermore National Laboratory (LLNL) has installed a state-of-the-art artificial intelligence (AI) accelerator from SambaNova Systems, the National Nuclear Security Administration (NNSA) announced today, allowing researchers to more effectively combine AI and machine learning (ML) with complex scientific workloads. LLNL has begun integrating the new AI hardware,…
Corona supercomputer gets funding for COVID-19 work
With funding from the Coronavirus Aid, Relief and Economic Security (CARES) Act, Lawrence Livermore National Laboratory (LLNL), chipmaker AMD and information technology company Supermicro have upgraded the supercomputing cluster Corona, providing additional resources to scientists for COVID-19 drug discovery and vaccine research. The recent addition of nearly 1,000 AMD…
Crucial electrical distribution system completed ahead of schedule, under budget
Construction crews recently wrapped up a long-anticipated electrical system upgrade that will supply Lawrence Livermore National Laboratory (LLNL) and neighboring Sandia/California with reliable, redundant underground power, completing it months ahead of schedule and well under budget. The first line-item project for LLNL in more than a decade, the Expand Electrical…
Webinar focuses on HPC for energy innovation initiative
In recognition of Manufacturing Day 2020 (MFG DAY) on Oct. 2, Lawrence Livermore National Laboratory (LLNL) will host a special online webinar to discuss the impact of the High Performance Computing for Energy Innovation (HPC4EI) initiative on American industrial competitiveness and energy savings. The virtual event begins at 8 a.m. PDT/11 a.m. EDT and is highlighted by a…
LLNL pairs world’s largest computer chip from Cerebras with Lassen to advance machine learning, AI research
Lawrence Livermore National Laboratory (LLNL) and artificial intelligence (AI) computer company Cerebras Systems have integrated the world’s largest computer chip into the National Nuclear Security Administration’s (NNSA’s) Lassen system, upgrading the top-tier supercomputer with cutting-edge AI technology. Technicians recently completed connecting the Silicon Valley-based…
Laboratory team completes highest-ever resolution quake simulations using Sierra supercomputer
A Lawrence Livermore National Laboratory (LLNL) team has published new supercomputer simulations of a magnitude 7.0 earthquake on the Hayward Fault. This work represents the highest-ever resolution ground motion simulations from such an event on this scale. The study used the SW4 code developed at LLNL. Simulations resolved rapidly varying shaking with broader band…
Using models, 3D printing to study common heart defect
One of the most common congenital heart defects, coarctation of the aorta (CoA) is a narrowing of the main artery transporting blood from the heart to the rest of the body. It affects more than 1,600 newborns each year in the United States, and can lead to health issues such as hypertension, premature coronary artery disease, aneurysms, stroke and cardiac failure. To…
Neuronal cultures advance ‘brain-on-a-chip’ technology
Lawrence Livermore National Laboratory (LLNL) researchers have increased the complexity of neuronal cultures grown on microelectrode arrays, a key step toward more accurately reproducing the cellular composition of the human brain outside the body. As described in a recently published paper in Scientific Reports, an LLNL team led by biomedical scientist Heather Enright…
Machine learning model may perfect 3D nanoprinting
Two-photon lithography (TPL) — a widely used 3D nanoprinting technique that uses laser light to create 3D objects — has shown promise in research applications but has yet to achieve widespread industry acceptance due to limitations on large-scale part production and time-intensive setup. Capable of printing nanoscale features at a very high resolution, TPL uses a laser…
LLNL papers accepted into prestigious conference
Two papers featuring Lawrence Livermore National Laboratory (LLNL) scientists were accepted in the 2020 International Conference on Machine Learning (ICML), one of the world’s premier conferences of its kind. The first, authored by three LLNL researchers, describes a new “mix-n-match” method for calibrating uncertainty of deep learning models. Uncertainty qualification is…
Lockdown doesn’t hinder annual Data Science Challenge
The COVID-19 pandemic and its subsequent restrictions on gatherings and travel have forced institutions and companies around the world to rethink how they offer their summer programs and internships, and Lawrence Livermore National Laboratory (LLNL) is no exception. This year’s Data Science Challenge with the University of California, Merced, the second such event of its…
Manufacturing, energy initiative to fund 11 new projects
The U.S. Department of Energy (DOE) today announced the recipients of the fall 2019 awards for the High Performance Computing for Energy Innovation (HPC4EI) initiative, including four newly funded projects led out of Lawrence Livermore National Laboratory. The 11 projects selected for a total of $3.3 million in funding under the High Performance Computing for Manufacturing…
Lab breaks ground for exascale facility upgrades
To meet the needs of tomorrow’s supercomputers, the National Nuclear Security Administration’s (NNSA’s) Lawrence Livermore National Laboratory (LLNL) has broken ground on its Exascale Computing Facility Modernization (ECFM) project, which will substantially upgrade the mechanical and electrical capabilities of the Livermore Computing Center. The upgrades will enable the…
Deep learning-based surrogate models outperform simulators and could hasten scientific discoveries
Surrogate models supported by neural networks can perform as well, and in some ways better, than computationally expensive simulators and could lead to new insights in complicated physics problems such as inertial confinement fusion (ICF), Lawrence Livermore National Laboratory (LLNL) scientists reported. In a paper published by the Proceedings of the National Academy of…
