Our research projects vary in size, scope, and duration, but they share a focus on developing tools and methods that help LLNL deliver on its missions to the nation and, more broadly, advance the state of the art in scientific HPC. Projects are organized here in three ways: Active projects are those currently funded and regularly updated. Legacy projects are no longer actively developed. The A-Z option sorts all projects alphabetically, both active and legacy.
LLNL’s Python 3–based ATS tool provides scientific code teams with automated regression testing across HPC architectures.
This project solves initial value problems for ODE systems, sensitivity analysis capabilities, additive Runge-Kutta methods, DAE systems, and nonlinear algebraic systems.
The RADIUSS project aims to lower cost and improve agility by encouraging adoption of our core open-source software products for use in institutional applications.
The Software Development Resource Center connects developers across LLNL through best practices in software tools, development methodologies, DevOps, security compliance, and more.
One of the most widely used tactical simulations in the world, JCATS is installed in hundreds of U.S. military and civilian organizations, in NATO, and in more than 30 countries.
The open-source MFEM library enables application scientists to quickly prototype parallel physics application codes based on PDEs discretized with high-order finite elements.
The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.
From molecular screening, a software platform, and an online data to the computing systems that power these projects.
LivIT tackles challenges of workforce safety, telecommuting, cybersecurity protocols, National Ignition Facility software updates, and more.
The Livermore Information Technology (LivIT) program is the first organization at LLNL to commit to migrating all services and applications to the Amazon Web Services cloud.
LLNL’s cyber programs work across a broad sponsor space to develop technologies addressing sophisticated cyber threats directed at national security and civilian critical infrastructure.
This project advances research in physics-informed ML, invests in validated and explainable ML, creates an advanced data environment, builds ML expertise across the complex, and more.
LC sited two different AI accelerators in 2020: the Cerebras wafer-scale AI engine attached to Lassen; and an AI accelerator from SambaNova Systems into the Corona cluster.
Upgraded with the C++ programming language, VBL provides high-fidelity models and high-resolution calculations of laser performance predictions.
The MAPP incorporates multiple software packages into one integrated code so that multiphysics simulation codes can perform at scale on present and future supercomputers.
LLNL is home to the world’s largest Spectra TFinityTM system, which offers the speed, agility, and capacity required to take LLNL into the exascale era.
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.
libROM is a library designed to facilitate Proper Orthogonal Decomposition (POD) based Reduced Order Modeling (ROM).
This 2021 R&D 100 award-winning software solves data center bottlenecks by enabling resource types, schedulers, and framework services to be deployed as data centers evolve.
A Livermore-developed programming approach helps software to run on different platforms without major disruption to the source code.
Supported by the Advanced Simulation and Computing program, Axom focuses on developing software infrastructure components that can be shared by HPC apps running on diverse platforms.
BUILD tackles the complexities of HPC software integration with dependency compatibility models, binary analysis tools, efficient logic solvers, and configuration optimization techniques.
StarSapphire is a collection of scientific data mining projects focusing on the analysis of data from scientific simulations, observations, and experiments.
Proxy apps serve as specific targets for testing and simulation without the time, effort, and expertise that porting or changing most production codes would require.