Topic: HPC Architectures

AMD will supply upgraded GPUs for the Corona supercomputing cluster, which will be used by scientists working on discovering potential antibodies and antiviral compounds for SARS-CoV-2.

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The White House announced the COVID-19 HPC Consortium to provide access to the world’s most powerful HPC resources that can advance the pace of scientific discovery in the fight to stop the virus.

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This week, LLNL highlighted one of the latest additions to its computing arsenal: Magma. Magma is a Penguin Computing “Relion” system comprised of 752 nodes with Intel Xeon Platinum 9242 processors.

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With its advanced CPUs/GPUs developed by AMD, El Capitan’s peak performance is expected to exceed 2 exaFLOPS, which would make it the fastest supercomputer in the world when it is deployed in 2023.

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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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LLNL is now home to the world’s largest Spectra TFinity system, following a complete replacement of the tape library hardware that supports Livermore’s data archives.

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The extreme-scale scientific software development kit (xSDK) is an ecosystem of independently developed math libraries and scientific domain components.

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The 2019 International Conference for High Performance Computing, Networking, Storage, and Analysis—SC19—returned to Denver. Once again LLNL made its presence known as a force in supercomputing.

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The HPCwire Editors’ and Readers’ Choice awards for Top Supercomputing Achievement recognized Cray, LLNL, and two other labs for developing the first U.S. exascale-class supercomputers.

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Penguin Computing announced that Corona, a high performance computing cluster delivered to LLNL in 2018, has been upgraded with the newest AMD Radeon Instinct MI60 accelerators.

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The latest TOP500 List of the world's most powerful computers was released at the International Supercomputing Conference for HPC, Networking, Storage and Analysis (SC19) in Denver.

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Penguin Computing, along with its partners Intel and CoolIT, has shipped LLNL's Linux-based cluster, known as “Magma,” to the Laboratory.

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In the third of three news features, LLNL-developed SCR software will contribute to the efficiency and effectiveness of the HPC leadership-class systems of tomorrow.

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In the second of three news features, LLNL-developed OpenZFS software will contribute to the efficiency and effectiveness of the HPC leadership-class systems of tomorrow.

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In the first of three news features, LLNL-developed Flux software will contribute to the efficiency and effectiveness of the HPC leadership-class systems of tomorrow.

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After years of preparation, LLNL’s upgraded Ares code runs a 98-billion-element simulation on 16,384 GPUs on the Sierra supercomputer.

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Cray, the DOE’s Exascale Computing Project, the DOE labs that will house the nation’s first three exascale supercomputers have established National Exascale Day to be celebrated annually (Oct. 18).

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LLNL's Lori Diachin, deputy director of the DOE's Exascale Computing Project, was one of three authorities on the topic of exascale computing to be interviewed and featured on builtin.com.

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The NNSA’s first exascale supercomputer, El Capitan, will have a peak performance of more than 1.5 exaflops (1.5 quintillion calculations per second) and an anticipated delivery in late 2022.

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Supercomputers have always been at the forefront of cooling technologies, with their high-power densities demanding careful attention. An LLNL team is upgrading facilities for exascale supercomputers.

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LLNL is home to several supercomputers, including Sierra, the world's second fastest. PCMag stopped by to find out how these computers handle virtual nuclear weapons tests and weather modeling.

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Next-generation computing systems are projected to surpass the speed of today's supercomputers by 5–10 times. This article explains OpenMP-relevant initiatives under the Exascale Computing Project.

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Users need tools that address the bottlenecks of exascale machines, work seamlessly with the programming models on the target machines, scale to the full size of the machine, provide the necessary automatic analysis capabilities, and be flexible and modular enough to overcome the complexities and changing demands of exascale architectures.

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Highlights include CASC director Jeff Hittinger's vision for the center as well as recent work with PruneJuice DataRaceBench, Caliper, and SUNDIALS.

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