Topic: Computational Science

LLNL is participating in the 35th annual Supercomputing Conference (SC23), which will be held both virtually and in Denver on November 12–17, 2023.

In recent years, the Lab has boosted its recruiting profile even further by offering the prestigious Sidney Fernbach Postdoctoral Fellowship in the Computing Sciences. The fellowship fosters creative partnerships between new and experienced scientists. In short, it ensures an annual cycle that refreshes advanced research in computer sciences at the Lab.

NIF Computing deploys regular updates to its computer control systems to ensure NIF continues to achieve ignition.

Hosted at LLNL, the Center for Efficient Exascale Discretizations’ annual event featured breakout discussions, more than two dozen speakers, and an evening of bocce ball.

With this year’s results, the Lab has now collected a total of 179 R&D 100 awards since 1978. The awards will be showcased at the 61st R&D 100 black-tie awards gala on Nov. 16 in San Diego.

A team from LLNL and seven other DOE labs is a finalist for the new ACM Gordon Bell Prize for Climate Modeling for running an unprecedented high-resolution global atmosphere model on the world’s first exascale supercomputer. 

LLNL's Ian Lee joins a Dots and Bridges panel to discuss HPC as a critical resource for data assimilation and numerical weather prediction research.

As part of the Exascale Computing Project’s ExaSGD project, a team including LLNL researchers ran HiOp, an open source optimization solver, on 9,000 nodes of Oak Ridge National Laboratory’s Frontier exascale supercomputer.

The event brought together 35 University of California students—ranging from undergraduates to graduate-level students from a diversity of majors—to work in groups to solve four key tasks, using actual electrocardiogram data to predict heart health.

Using explainable artificial intelligence techniques can help increase the reach of machine learning applications in materials science, making the process of designing new materials much more efficient.

With simple mathematical modifications to a common model of clouds and turbulence, LLNL scientists and their collaborators helped minimize nonphysical results.

From wind tunnels and cardiovascular electrodes to the futuristic world of exascale computing, Brian Gunney has been finding solutions for unsolvable problems.

Responding to a DOE grid optimization challenge, an LLNL-led team developed the mathematical, computational, and software components needed to solve problems of the real-world power grid.

Computer scientist Vanessa Sochat talks to BSSw about a recent effort to survey software developer needs at LLNL.

Open-source software has played a key role in paving the way for LLNL's ignition breakthrough, and will continue to help push the field forward.

For the physicists, computer scientists, and code developers who have worked on fusion for decades, computer simulations have been inexorably tied to the National Ignition Facility’s quest for ignition.

libROM is a library designed to facilitate Proper Orthogonal Decomposition (POD) based Reduced Order Modeling (ROM).

The prestigious fellow designation is a lifetime honorific title and honors SIAM members who have made outstanding contributions to fields served by the organization.

The new model addresses a problem in simulating RAS behavior, where conventional methods come up short of reaching the time- and length-scales needed to observe biological processes of RAS-related cancers.

A new component-wise reduced order modeling method enables high-fidelity lattice design optimization.

A principal investigator at LLNL shares how machine learning on the world’s fastest systems catalyzed the lab’s breakthrough.

Collaborative autonomy software apps allow networked devices to detect, gather, identify and interpret data; defend against cyber-attacks; and continue to operate despite infiltration.

A high-fidelity, specialized code solves partial differential equations for plasma simulations.

A new collaboration will leverage advanced LLNL-developed software to create a “digital twin” of the near-net shape mill-products system for producing aerospace parts.

High performance computing was key to the December 5 breakthrough at the National Ignition Facility.