Topic: Performance, Portability, and Productivity

Over the next three years, CASC researchers and collaborators will integrate LLMs into HPC software to boost performance and sustainability.

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The latest issue of LLNL's magazine explains how the world’s most powerful supercomputer helps scientists safeguard the U.S. nuclear stockpile.

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The Association for Computing Machinery's (ACM) Special Interest Group on High Performance Computing (SIGHPC) has awarded Kathryn Mohror with its prestigious Emerging Woman Leader in Technical Computing (EWLTC) Award.

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Collecting variants in low-level hardware features across multiple GPU and CPU architectures.

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Two LLNL teams have come up with ingenious solutions to a few of the more vexing difficulties. For their efforts, they’ve won awards coveted by scientists in the technology fields.

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Discover how the software architecture and storage systems that will drive El Capitan’s performance will help LLNL and the NNSA Tri-Labs push the boundaries of computational science.

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LLNL researchers have achieved a milestone in accelerating and adding features to complex multiphysics simulations run on GPUs, a development that could advance HPC and engineering.

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The Tools Working Group delivers debugging, correctness, and performance analysis solutions at an unprecedented scale.

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With this year’s results, the Lab has now collected a total of 179 R&D 100 awards since 1978. The awards will be showcased at the 61st R&D 100 black-tie awards gala on Nov. 16 in San Diego.

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LLNL's zfp and Variorum software projects are winners. LLNL is a co-developing organization on the winning CANDLE project.

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Siting a supercomputer requires close coordination of hardware, software, applications, and Livermore Computing facilities.

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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.

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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 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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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 different platforms.

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