Topic: HPC Systems and Software

The Center for Non-Perturbative Studies of Functional Materials under Non-Equilibrium Conditions advances high performance computing software to support novel materials discovery.

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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, the open-source Axom project focuses on developing software infrastructure components that can be shared by HPC applications running on diverse computing platforms.

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Our use of supercomputers is enabled by the codes developed to model and simulate complex physical phenomena on massively parallel architectures.

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Livermore researchers have developed a toolset for solving data center bottlenecks. Flux offers a framework that enables new resource types, schedulers, and framework services to be deployed as data centers continue to evolve.

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LLNL participates in the digital ISC High Performance Conference (ISC21) on June 24 through July 2.

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This video describes Flux, an open-source software framework that manages and schedules computing workflows to maximize available resources to run applications faster and more efficiently.

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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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In a talk recorded for the 2020 LLNL Computing Virtual Expo, Computing principal deputy associate director and ECP deputy director Lori Diachin describes the ECP’s goals and the Laboratory's role.

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LLNL, IBM and Red Hat are combining forces to develop best practices for interfacing HPC schedulers and cloud orchestrators, an effort designed to prepare for emerging supercomputers that take advantage of cloud technologies.

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Computing relies on engineers like Stephanie Brink to keep the legacy codes running smoothly. “You’re only as fast as your slowest processor or your slowest function,” says Brink, who works in CASC. By analyzing a legacy code’s performance, Brink and her team can reduce the amount of time it takes to run and allow for more critical science to be accomplished.

People Highlight

LLNL is looking for participants and attendees from industry, research institutions and academia for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10. The event is sponsored by LLNL’s High Performance Computing Innovation Center and the Data Science Institute.

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LLNL has turned to AMD and Penguin Computing to upgrade a supercomputer to help in the fight against the novel coronavirus. The computer's name is... Corona. The 2018 system, named for the total solar eclipse of 2017, will nearly double in peak performance to 4.5 peak petaflops.

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The hypre team's latest work gives scientists the ability to efficiently utilize modern GPU-based extreme scale parallel supercomputers to address many scientific problems.

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This project aims to tackle the complexities of HPC software integration with dependency compatibility models, binary analysis tools, efficient logic solvers, and configuration optimization techniques.

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The HPC industry publication HPCwire named Bronis R. de Supinski, LLNL’s chief technology officer for Livermore Computing, as one of its People to Watch for 2021.

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COVID-19 HPC Consortium scientists and stakeholders met virtually to mark the consortium’s one-year anniversary, discussing the progress of research projects and the need to pursue a broader organization to mobilize supercomputing access for future crises.

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In his opening keynote address at the AI Systems Summit, LLNL CTO Bronis de Supinski described integration of two AI-specific systems to achieve system level heterogeneity.

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In recognition of March as International Women’s History Month, SC21 profiled six women doing trailblazing work, including LLNL's Hiranmayi Ranganathan.

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CTO Bronis de Supinski discusses the integrated storage strategy of the future El Capitan exascale supercomputing system, which will have in excess of 2 exaflops of raw computing power spread across nodes.

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Our researchers will be well represented at the virtual SIAM Conference on Computational Science and Engineering (CSE21) on March 1–5. SIAM is the Society for Industrial and Applied Mathematics with an international community of more than 14,500 individual members.

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A near node local storage innovation called Rabbit factored heavily into LLNL’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan.

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