Topic: Collaborations

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.

A multidecade, multi-laboratory collaboration evolves scalable long-term data storage and retrieval solutions to survive the march of time.

Combining specialized software tools with heterogeneous HPC hardware requires an intelligent workflow performance optimization strategy.

Highlights include MFEM community workshops, compiler co-design, HPC standards committees, and AI/ML for national security.

Presented at the 2022 International Conference on Computational Science, the team’s research introduces metrics that can improve the accuracy of blood flow simulations.

A Sandia National Laboratories team has adapted Livermore’s software.llnl.gov website to showcase their own open-source software. Both projects are developed and hosted on GitHub.

The Earth System Grid Federation is a web-based tool set that powers most global Earth system research.

Livermore’s archive leverages a hierarchical storage management application that runs on a cluster architecture that is user-friendly, extremely scalable, and lightning fast.

El Capitan will have a peak performance of more than 2 exaflops—roughly 16 times faster on average than the Sierra system—and is projected to be several times more energy efficient than Sierra.

The MAPP incorporates multiple software packages into one integrated code so that multiphysics simulation codes can perform at scale on present and future supercomputers.

Upgraded with the C++ programming language, VBL provides high-fidelity models and high-resolution calculations of laser performance predictions.

ADAPD integrates expertise from DOE national labs to analyze growing global data streams and traditional intelligence data, enabling early warning of nuclear proliferation activities.

Livermore researchers are enhancing HARVEY, an open-source parallel fluid dynamics application designed to model blood flow in patient-specific geometries.