HPC News

LLNL physicists designing new laser systems and modeling laser performance now have a powerful new tool in their hands with the Virtual Beam Line++ (VBL++) code.

Computer scientists, biomedical engineers, cancer biologists and bioinformaticians from eight Department of Energy (DOE) national laboratories, health-related government agencies and universities converged at Lawrence Livermore National Laboratory (LLNL) March 6-7 to discuss ongoing efforts to advance cancer research through computation, identify existing challenges and brainstorm future multidisciplinary projects.

LNL’s Center for Applied Scientific Computing (CASC) and Livermore Computing divisions recently joined forces to tackle performance drag caused by input/output (I/O) workloads.

The Department of Energy's (DOE) High Performance Computing for Energy Innovation (HPC4EI) Initiative has issued its first joint solicitation for the High Performance Computing for Manufacturing Program (HPC4Mfg) and the High Performance Computing for Materials Program (HPC4Mtls).

The call for proposals seeks American companies interested in collaborating with DOE’s national laboratories on one-year projects to apply high-performance computing (HPC) modeling, simulation and data analysis to key challenges in U.S. manufacturing and material development.

Lawrence Livermore National Laboratory, in partnership with Penguin Computing, AMD and Mellanox Technologies, will accept delivery of Corona, a new unclassified high-performance computing (HPC) cluster that will provide unique capabilities for Lab researchers and industry partners to explore data science, machine learning and big data analytics.

Sierra, one of the fastest supercomputers in the world, will serve the National Nuclear Security Administration’s three nuclear security laboratories, providing high-fidelity simulations in support of NNSA’s core mission of ensuring the safety, security and effectiveness of the nation’s nuclear stockpile. [VIDEO]

A multi-institutional team of scientists and engineers plan to simultaneously challenge DOE’s supercomputing resources, advance artificial intelligence capabilities and enable a precision medicine approach for TBI.

In an audio discussion, HI Director Terri Quinn (Lawrence Livermore National Laboratory) describes how HI performs its mission and what its top goals are.

After four years of development, the Energy Exascale Earth System Model (E3SM) will be released to the broader scientific community this month.

Machine learning models developed at LLNL in conjunction with Kaiser Permanente can more accurately characterize a patient's progression through the stages of sepsis.

The Department of Energy (DOE (link is external)) on Feb. 1 announced up to $3 million will be available to U.S. manufacturers for public/private projects aimed at applying high performance computing to industry challenges for the advancement of energy innovation.

The Department of Energy’s (DOE) Office of Fossil Energy (FE) today announced the funding of $450,000 for the first two private-public partnerships under a brand-new initiative aimed at discovering, designing and scaling up production of novel materials for severe environments.

Work is moving fast and furious in the Livermore Computing Complex at Lawrence Livermore National Laboratory (LLNL), where siting and installation for Sierra, the Lab’s next advanced technology high-performance supercomputer, is kicking into high gear.

Livermore physicist Jon Belof and a team of physicists, engineers, and computational scientists are subjecting matter to extreme conditions and simulating experiments with high-performance computers to study phase transitions at ultrahigh pressures.

Paper-making research, performed for an HPC4Manufacturing (HPC4Mfg) project with the papermaking giant, Proctor and Gamble, resulted in the largest multi-scale model of paper products to date, simulating thousands of fibers in ParaDyn with resolution down to the micron scale.

Sandia researchers modeled the electromagnetics of complex systems on two DOE supercomputers that can solve tens of millions of problems in hours: Trinity (LANL) and Sequoia (LLNL). This research has led to impressive advances in metamaterials research that will boost the substances’ flexibility, efficiency, adaptability and other properties.

To address the challenges of transitioning to the next generation of high performance computing (HPC), Livermore is bringing together designers of hardware, software, and applications to rethink and redesign their HPC elements and interactions for the exascale era (i.e., systems capable of a billion billion floating point operations per second or 1018 flops).

The DOE's High Performance Computing for Manufacturing (HPC4Mfg) Program aims to advance clean-energy technologies, increase the efficiency of manufacturing processes, accelerate innovation, reduce the time it takes to bring new technologies to market, and improve the quality of products. The program unites the world-class high-performance computing (HPC) resources and expertise of Lawrence Livermore and other national laboratories with U.S. manufacturers to deliver solutions that could revolutionize the manufacturing industry.

A historic partnership between the Department of Energy (DOE) and the National Cancer Institute (NCI) is applying the formidable computing resources at Livermore and other DOE national laboratories to advance cancer research and treatment. The effort will help researchers and physicians better understand the complexity of cancer, choose the best treatment options for every patient, and reveal possible patterns hidden in vast patient and experimental data sets.

Lawrence Livermore National Laboratory (LLNL) was one of four national labs selected to lead a "co-design" center by the Department of Energy's Exascale Computing Project (link is external) (ECP) as part of a four-year, $48 million funding award. Each co-design center will receive $3 million annually. LLNL's Tzanio Kolev is the director of the newly established ECP co-design Center for Efficient Exascale Discretizations (CEED). "Co-design" refers to the collaborative and interdisciplinary engineering process for developing capable exascale systems.

A U.S. Department of Energy (DOE) program designed to spur the use of high performance supercomputers to advance U.S. manufacturing has funded 13 new industry projects for a total of $3.8 million. Experts at Lawrence Livermore and other DOE national laboratories will work directly with manufacturing industry members to teach them how to adopt or advance their use of high performance computing (HPC) to address manufacturing challenges with a goal of increasing energy efficiency, reducing environmental impacts, and advancing clean energy technologies.

Lawrence Livermore National Laboratory (LLNL) and partners announced 10 new industry projects to advance manufacturing using high-performance computing (HPC) under a DOE program. Industry projects ranging from improved turbine blades for aircraft engines and reduced heat loss in electronics to waste reduction in paper manufacturing and improved fiberglass production are among the first to be selected for funding and partnerships with national labs under the U.S. Department of Energy's (DOE) High Performance Computing for Manufacturing (HPC4Mfg) Program. LLNL leads the program and partners with Lawrence Berkeley and Oak Ridge National Laboratories (LBNL and ORNL).

Each of the 10 Phase I projects will be funded at approximately $300,000 for a total of just under $3 million. Selected companies will partner with national labs, which will provide expertise in and access to high performance computing systems aimed at high-impact challenges. The Advanced Manufacturing Office (AMO) within DOE's Office of Energy Efficiency and Renewable Energy (EERE) created this program to advance clean energy technologies, increase the efficiency of manufacturing processes, accelerate innovation, shorten the time it takes to bring new technologies to market, and improve the quality of products.

Livermore scientists and collaborators accomplish three-dimensional, high-resolution simulations of whole-body blood flow on 1,572,864 cores of Blue Gene/Q, also known as Sequoia. Blood flow simulations of hemodynamics in the systemic arterial tree can potentially have a tremendous impact on the diagnosis and treatment of patients suffering from vascular disease.