![]() “Building on our strong foundation in high-performance computing and adding transformative coherency capabilities, AMD is enabling the NNSA Tri-Lab community - LLNL, Los Alamos and Sandia national laboratories - to achieve their mission-critical objectives and contribute new AI advancements to the industry. “El Capitan will drive unprecedented advancements in HPC and AI, powered by the next-generation AMD EPYC CPUs and Radeon Instinct GPUs,” said Forrest Norrod, senior vice president and general manager, Datacenter and Embedded Systems Group, AMD. ![]() The use of AMD’s GPUs also is anticipated to dramatically increase El Capitan’s energy efficiency as compared to systems using today’s graphical processors. These workloads will supplement scientific models that researchers hope will be faster, more accurate and intrinsically capable of quantifying uncertainty in their predictions, and will be increasingly used for stockpile stewardship applications. El Capitan’s graphics processors will be amenable to AI and machine learning-assisted data analysis, further propelling LLNL’s sizable investment in AI-driven scientific workloads. ![]() Naturally, this has required an intimate, sustained partnership with our industry technology partners and between the tri-labs to be successful.”Īnticipated to be one of the most capable supercomputers in the world, El Capitan will have a significantly greater per-node capability than any current systems, LLNL researchers said. “And our teams and industrial partners will deliver this capability as planned to the nation. “We have been pursuing a balanced investment effort at NNSA in advancing our codes, our platforms and our facilities in an integrated and focused way,” said Michel McCoy, Weapon Simulation and Computing Program Director at LLNL. This enables LLNL scientists to run high-resolution 3D models quicker, as well as increase the fidelity and repeatability of calculations, thus making those simulations truer to life. Providing enormous computation capability for the energy used, the GPUs will provide the majority of the peak floating-point performance of El Capitan. The nodes will support simulations used by the NNSA labs to address the demands of the LEPs, whose computational requirements are growing due to the ramping up of stockpile modernization efforts and in response to rapidly evolving threats from America’s adversaries. “Today’s news provides a prime example of how government and industry can work together for the benefit of the entire nation.”Įl Capitan will be powered by next-generation AMD EPYC processors, code-named “Genoa” and featuring the “Zen 4” processor core, next-generation AMD Radeon Instinct GPUs based on a new compute-optimized architecture for workloads including HPC and AI, and the AMD Radeon Open Compute platform (ROCm) heterogenous computing software. “This unprecedented computing capability, powered by advanced CPU and GPU technology from AMD, will sustain America’s position on the global stage in high-performance computing and provide an observable example of the commitment of the country to maintaining an unparalleled nuclear deterrent,” said LLNL Director Bill Goldstein. (An exaFLOP is one quintillion floating point operations per second.)įunded by the Advanced Simulation and Computing (ASC) program at the Department of Energy’s (DOE) NNSA, El Capitan will perform complex and increasingly predictive modeling and simulation for NNSA’s vital Life Extension Programs (LEPs), which address weapons aging and emergent threat issues in the absence of underground nuclear testing. With its advanced computing and graphics processing units (CPUs/GPUs), El Capitan’s peak performance is expected to exceed 2 exaFLOPS, ensuring the National Nuclear Security Administration (NNSA) laboratories - LLNL, Sandia National Laboratories and Los Alamos National Laboratory - can meet their primary mission of keeping the nation’s nuclear stockpile safe, secure and reliable. (AMD) today announced the selection of AMD as the node supplier for El Capitan, projected to be the world’s most powerful supercomputer when it is fully deployed in 2023. Lawrence Livermore National Laboratory (LLNL), Hewlett Packard Enterprise (HPE) and Advanced Micro Devices Inc.
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