Topic: Collaborations

SC24, held recently in Atlanta, was a landmark event, setting new records and demonstrating LLNL's unparalleled contributions to HPC innovation and impact.

Drawing more than 300 attendees, this year’s “D3” workshop focused on tackling pressing data challenges in nuclear security, energy and collaborative scientific discovery, and featured a host of talks, presentations and panels.

Oxide Cloud Computer installation at Livermore Computing's HPC center modernizes on-premises cloud computing capabilities for general purpose workloads.

The NNSA’s exascale milestone is possible only through successful industry partnerships. Hewlett Packard Enterprise staff share their experiences working with LLNL.

Developed by LLNL, Colorado, and Purdue researchers, a new approach eases the implementation of curved geometries into computing simulations.

The proposed Frontiers in Artificial Intelligence for Science, Security and Technology (FASST) initiative will advance national security; attract and build a talented workforce; harness AI for scientific discovery; address energy challenges; develop technical expertise necessary for AI governance.

Developed by LLNL and Portland State University researchers, innovative matrix-free solvers offer performance gains for complex multiphysics simulations.

In a milestone for supercomputing-aided drug design, LLNL and BridgeBio Oncology Therapeutics today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer.

Release the codes! With a dynamic developer community and a long history of encouraging open-source software, LLNL has reached quadruple-digit GitHub offerings.

In a groundbreaking development for addressing future viral pandemics, a multi-institutional team involving LLNL researchers has successfully combined an AI-backed platform with supercomputing to redesign and restore the effectiveness of antibodies whose ability to fight viruses has been compromi

The El Capitan Center of Excellence provides a conduit between national labs and commercial vendors, ensuring that the exascale system will meet everyone’s needs.

An LLNL-led effort that performed an unprecedented global climate model simulation on the world’s first exascale supercomputer has won the first-ever Association for Computing Machinery (ACM) Gordon Bell Prize for Climate Modelling, ACM officials announced.

Data researchers, developers, data managers, and program managers from national laboratories visited LLNL to discuss the latest in data management, sharing, and accessibility at the 2023 DOE Data Days (D3) workshop.

The Center for Efficient Exascale Discretizations has developed innovative mathematical algorithms for the DOE’s next generation of supercomputers.

Led by Argonne National Lab and including an LLNL collaborator, a research team aims to provide the security necessary to study life-threatening medical issues without violating patient privacy.

The Tri-Lab Operating System Stack (TOSS) ensures other national labs’ supercomputing needs are met.

Innovative hardware provides near-node local storage alongside large-capacity storage.

Livermore Computing is making significant progress toward siting the NNSA’s first exascale supercomputer.

This issue highlights some of CASC’s contributions to making controlled laboratory fusion possible at the National Ignition Facility.

A research team from Oak Ridge and Lawrence Livermore national labs won the first IPDPS Best Open-Source Contribution Award for the paper “UnifyFS: A User-level Shared File System for Unified Access to Distributed Local Storage.”

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

Lori Diachin will take over as director of the DOE’s Exascale Computing Project on June 1, guiding the successful, multi-institutional high performance computing effort through its final stages.

Since 2018, the Lab has seen tremendous growth in its data science community and has invested heavily in related research. Five years later, the Data Science Institute has found its stride.

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

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.