Topic: Open-Source Software

Unique among data compressors, zfp is designed to be a compact number format for storing data arrays in-memory in compressed form while still supporting high-speed random access.

Variorum provides robust, portable interfaces that allow us to measure and optimize computation at the physical level: temperature, cycles, energy, and power. With that foundation, we can get the best possible use of our world-class computing resources.

Updating a compiler can affect how code runs, leading to inconsistencies in outputs and creating problems for scientists. A new tool automatically finds the sources of these inconsistencies.

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

An LLNL Distinguished Member of Technical Staff, Falgout is still finding the fun in problem solving as project leader for two of CASC’s most cutting-edge multigrid method computing projects, hypre and XBraid.

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.

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

LC’s adaptation of OpenZFS software provides high performance parallel file systems with better performance and scalability.

UCLA's Institute for Pure & Applied Mathematics hosted LLNL's Tzanio Kolev for a talk about high-order finite element methods.

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

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.

The second annual MFEM workshop brought together the project’s global user and developer community for technical talks, Q&A, and more.

This project solves initial value problems for ODE systems, sensitivity analysis capabilities, additive Runge-Kutta methods, DAE systems, and nonlinear algebraic systems.

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.

An LLNL Distinguished Member of Technical Staff, Todd Gamblin leads the Spack project, an open-source package manager with a rapidly growing global community that has changed the way people use HPC software.

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 climate change research.

Winning the best paper award at PacificVis 2022, a research team has developed a resolution-precision-adaptive representation technique that reduces mesh sizes, thereby reducing the memory and storage footprints of large scientific datasets.

LLNL’s Python 3–based ATS tool provides scientific code teams with automated regression testing across HPC architectures.

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.

Computational mathematician Julian Andrej began using LLNL-developed, open-source software while in Germany. Now at Livermore, he lends his expertise to the Center for Applied Scientific Computing, developing code for next-generation computing hardware.

From molecular screening, a software platform, and an online data to the computing systems that power these projects.

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

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.