Topic: Computational Science

Computer scientists, biomedical engineers, cancer biologists, and bioinformaticians from 8 DOE labs, health agencies, and universities advance cancer research through computation.

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In this video from the 2019 Stanford HPC Conference, LLNL's Rob Neely presents "Sierra – Science Unleashed." Sierra is NNSA’s first large-scale production heterogeneous system.

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The HPC for Manufacturing Program (HPC4Mfg) announced the recipients of $1.2 million in federal funding for projects aimed at solving key manufacturing challenges through supercomputing.

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Held in Washington, DC, the Earth System Grid Federation’s 8th annual face-to-face conference was a lively, fruitful affair.

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LLNL heads to the SIAM Conference on Computational Science and Engineering (CSE19) in Spokane, Washington, on February 25 to March 1, 2019.

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The “best in class” award was for the Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium, which aims to use HPC to accelerate drug development.

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In this career profile, CASC architect Tom Epperly describes NIF's Virtual Beam Line code and his penchant for solving software programming problems.

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LLNL has successfully deployed power distribution grid simulation software on an HPC system, taking a key step toward creating a commercial tool that utilities could use to modernize the grid.

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Highlights include debris an 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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In response to a DOE grid optimization challenge, the LLNL-led gollnlp team is developing 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.

People Highlight

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

People Highlight

Highlights include Computation’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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The code GEFIE-QUAD (gratings electric field integral equation on quadrilateral grids) is a first-principles simulation method to model the interaction of laser light with diffraction gratings, and to determine how grating imperfections can affect the performance of the compressor in a CPA laser system. GEFIE-QUAD gives scientists a powerful simulation tool to predict the performance of a realistic 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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The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.

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

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PDES focuses on models that can accurately and effectively simulate California’s large-scale electric grid.

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Livermore researchers have developed an algorithm for the numerical solution of a phase-field model of microstructure evolution in polycrystalline materials. The system of equations includes a local order parameter, a quaternion representation of local orientation, and species composition. The approach is based on a finite volume discretization and an implicit time-stepping algorithm. Recent developments have been focused on modeling solidification in binary alloys, coupled with CALPHAD methodology.

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LLNL researchers are developing a truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems of sizes that were previously impossible with this degree of accuracy.

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High-resolution finite volume methods are being developed for solving problems in complex phase space geometries, motivated by kinetic models of fusion plasmas.

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