Topic: Computational Science

LLNL researchers have identified an initial set of therapeutic antibody sequences, designed using machine learning and supercomputing, aimed at binding and neutralizing SARS-CoV-2.

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Alyson Fox is a math geek. She has three degrees in the subject—including a Ph.D. in Applied Mathematics from the University of Colorado at Boulder—and her passion for solving complex challenges drives her work at LLNL’s Center for Applied Scientific Computing (CASC).

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The early-March event was the third annual WiDS Livermore event, featuring speakers, a career panel, mentoring, and a livestream.

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LLNL has infrastructure, unique research capabilities, and a dedicated team of scientists and engineers supporting the fight against COVID-19.

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LLNL scientists are contributing to the global fight against COVID-19 by combining AI/ML, bioinformatics, and supercomputing to help discover candidates for new antibodies and pharmaceutical drugs.

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The White House announced the COVID-19 HPC Consortium to provide access to HPC resources that can advance scientific discovery in the fight to stop the virus.

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LLNL bested more than two dozen teams to place first overall in Challenge 1 of the DOE Grid Optimization Competition, aimed at developing a more reliable, resilient, and secure U.S. electrical grid.

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On January 31, 2020, the Sequoia supercomputer and its file system were decommissioned after nearly 8 years of remarkable service and achievements.

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Laser-fusion researchers have turned to machine-learning techniques to seek the combinations of laser pulse characteristics and target design needed to optimize target implosions for ICF.

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A multi-institutional consortium aims to speed up the drug discovery pipeline by building predictive, data-driven pharmaceutical models.

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Jorge Castro Morales likes having different responsibilities at work. He says, “I’m honored to be working with a diverse team of multidisciplinary experts to resolve very complex problems on a daily basis.”

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Computational Scientist Ramesh Pankajakshan came to LLNL in 2016 directly from the University of Tennessee at Chattanooga. But unlike most recent hires from universities, he switched from research professor to professional researcher.

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Highlights include perspectives on machine learning and artificial intelligence in science, data driven models, autonomous vehicle operations, and the OpenMP standard 5.0.

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Simulation workflows for ALE methods often require a manual tuning process. We are developing novel predictive analytics for simulations and an infrastructure for integration of analytics.

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Highlights include debris and shrapnel modeling at NIF, scalable algorithms for complex engineering systems, magnetic fusion simulation, and data placement optimization on GPUs.

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AIMS (Analytics and Informatics Management Systems) develops integrated cyberinfrastructure for big climate data discovery, analytics, simulations, and knowledge innovation.

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Responding to a DOE grid optimization challenge, an LLNL-led team developed the mathematical, computational, and software components needed to solve problems of the real-world power grid.

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Highlights include complex simulation codes, uncertainty quantification, discrete event simulation, and the Unify file system.

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When computer scientist Gordon Lau arrived at Lawrence Livermore more than 20 years ago, he was a contractor assigned to a laser isotope separation project.

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The NIF Computing team plays a key role in this smoothly running facility, and computer scientist Joshua Senecal supports multiple operational areas.

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Highlights include the directorate's annual external review, machine learning for ALE simulations, CFD modeling for low-carbon solutions, seismic modeling, and an in-line floating point compression tool.

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This first-principles simulation method models the interaction of laser light with diffraction gratings, giving scientists a powerful tool to predict the performance of a laser compressor.

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Highlights include the HYPRE library, recent data science efforts, the IDEALS project, and the latest on the Exascale Computing Project.

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