Topic: HPC Architectures

The Lab was already using Elastic components to gather data from its HPC clusters, then investigated whether Elasticsearch and Kibana could be applied to all scanning and logging activities across the board.

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An LLNL Distinguished Member of Technical Staff, Gokhale is considered an expert in her field, and continues to enjoy the fast pace of innovation and change in computing.

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Supercomputers broke the exascale barrier, marking a new era in processing power, but the energy consumption of such machines cannot run rampant.

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UCLA's Institute for Pure & Applied Mathematics hosted LLNL's Erik Draeger for a talk about the challenges and possibilities of exascale computing.

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ASC’s Advanced Memory Technology research projects are developing technologies that will impact future computer system architectures for complex modeling and simulation workloads.

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The 2022 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22) returned to Dallas as a large contingent of LLNL staff participated in sessions, panels, paper presentations and workshops centered around HPC.

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Science & Technology Review highlights the Exascale Computing Facility Modernization project that delivered the infrastructure required to bring exascale computing online in 2023.

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The Exascale Computing Project has compiled a playlist of videos from multiple national labs to highlight the impacts of exascale computing.

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While LLNL awaits the arrival of El Capitan, physicists and computer scientists running scientific applications on testbeds are getting a taste of what to expect.

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Climate change can bring not only heat, but also increased humidity, reducing the efficiency of the evaporative coolers many HPC centers rely on.

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Preparing the Livermore Computing Center for El Capitan and the exascale era of supercomputers required an entirely new way of thinking about the facility’s mechanical and electrical capabilities.

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The second article in a series about the Lab's stockpile stewardship mission highlights computational models, parallel architectures, and data science techniques.

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The first article in a series about the Lab's stockpile stewardship mission highlights the roles of computer simulations and exascale computing.

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The new oneAPI Center of Excellence will involve the Center for Applied Scientific Computing and accelerate ZFP compression software to advance exascale computing.

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LLNL participates in the CMD-IT/ACM Richard Tapia Celebration of Diversity in Computing Conference (Tapia2022) on September 7–10.

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LLNL has signed a memorandum of understanding with HPC facilities in Germany, the United Kingdom, and the U.S., jointly forming the International Association of Supercomputing Centers.

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An LLNL team will be among the first researchers to perform work on the world’s first exascale supercomputer—Oak Ridge National Laboratory’s Frontier—when they use the system to model cancer-causing protein mutations.

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The Lab's upcoming exascale-capable supercomputer will see an implementation of a converged accelerated computing unit, or APU, hybrid CPU-GPU compute engine.

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In a presentation delivered to the 79th HPC User Forum at Oak Ridge National Laboratory, LLNL's Terri Quinn revealed that AMD’s forthcoming MI300 APU would be the computational bedrock of El Capitan, which is slated for installation at LLNL in late 2023.

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The utility-grade infrastructure project massively upgraded the power and water-cooling capacity of the adjacent Livermore Computing Center, preparing it to house next generation exascale-class supercomputers for NNSA.

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As the U.S. welcomed the world’s first “true” exascale supercomputer, three predecessor machines for LLNL's future exascale system El Capitan managed to rank highly on the latest Top500 List of the world’s most powerful supercomputers.

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LLNL participates in the International Parallel and Distributed Processing Symposium (IPDPS) on May 30 through June 3.

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Technologies developed through the Next-Generation High Performance Computing Network project are expected to support mission-critical applications for HPC, AI and ML, and high performance data analytics.

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