Topic: Open-Source Software

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.

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

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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.

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The Exascale Computing Project (ECP) 2022 Community Birds-of-a-Feather Days will take place May 10–12 via Zoom. The event provides an opportunity for the HPC community to engage with ECP teams to discuss our latest development efforts.

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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.

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The Livermore Computing–developed Flux project addresses challenges posed by complex scientific research supercomputing workflows.

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The Department of Energy's Office of Science interviewed LLNL computer scientist Peter Lindstrom about his work since receiving the 2011 Early Career Award.

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

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

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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.

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LLNL researchers and collaborators have developed a highly detailed, ML–backed multiscale model revealing the importance of lipids to RAS, a family of proteins whose mutations are linked to many cancers.

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The MFEM software library provides high-order mathematical algorithms for large-scale scientific simulations. An October workshop brought together MFEM’s global user and developer community for the first time.

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Held virtually on July 15, our fifth annual Developer Day featured lightning talks, a technical deep dive, “quick takes” on remote-development resources, presentations about career paths, and a career development panel discussion.

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A Livermore-developed programming approach helps software to run on different platforms without major disruption to the source code.

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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.

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Computer scientist Vanessa Sochat isn’t afraid to meet new experiences head on. With a Stanford PhD and a jump-right-in attitude, she joined LLNL to work on the BUILD project, Spack package manager, and other open-source initiatives.

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fpzip is a library for lossless or lossy compression of multidimensional floating-point arrays. It was primarily designed for lossless compression.

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The SAMRAI library is the code base in CASC for exploring application, numerical, parallel computing, and software issues associated with structured adaptive mesh refinement.

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The Maestro Workflow Conductor is a lightweight, open-source Python tool that can launch multi-step software simulation workflows in a clear, concise, consistent, and repeatable manner.

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FGPU provides code examples that port FORTRAN codes to run on IBM OpenPOWER platforms like LLNL's Sierra supercomputer.

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The hypre library's comprehensive suite of scalable parallel linear solvers makes large-scale scientific simulations possible by solving problems faster.

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