AMD CPUs and Radeon GPUs Enable El Capitan Supercomputer to Break 2 Exaflops Barrier

El Capitan is set to be the second all AMD CPU and GPU exascale system in the U.S.

El Capitan is set to be the second all AMD CPU and GPU exascale system in the U.S.

AMD has joined Lawrence Livermore National Laboratory (LLNL) and HPE, in announcing that El Capitan, the upcoming exascale class supercomputer at LLNL, will be powered by next-generation AMD EPYC CPUs, AMD Radeon Instinct graphics processing units and open-source AMD ROCm heterogeneous computing software. 

With delivery expected in early 2023, the El Capitan system is expected to be an exceptionally fast supercomputer with more than 2 exaflops of double precision performance. This performance will support National Nuclear Security Administration (NNSA) requirements for its primary mission of ensuring the safety, security and reliability of the nation’s nuclear stockpile.

The AMD-based nodes will be optimized to accelerate artificial intelligence (AI) and machine learning (ML) workloads to potentially enable the expanded use of AI and ML into the research, computational techniques and analysis that benefits NNSA missions.

“El Capitan will drive unprecedented advancements in HPC and AI, powered by the next generation AMD EPYC CPUs and Radeon Instinct GPUs,” says Forrest Norrod, senior vice president and general manager, Datacenter and Embedded Systems Group, AMD. “Building on our strong foundation in high-performance computing and adding transformative coherency capabilities, AMD is enabling the NNSA Tri-Lab community—LLNL and the Los Alamos and Sandia national laboratories—to achieve their mission critical objectives and contribute new AI advancements to the industry.”

AMD Technology Powering El Capitan

AMD is applying its experience from the high-performance computing industry and advancing its existing CPU and GPU designs for El Capitan, enabling the system to be architected for maximum performance and ease of use.

AMD technology within El Capitan includes:

  • Next-generation AMD EPYC processors, codenamed “Genoa” featuring the “Zen 4” processor core. These processors will support next-generation memory and I/O sub systems for AI and HPC workloads.
  • Next-generation Radeon Instinct GPUs based on a new compute-optimized architecture for workloads including HPC and AI. These GPUs will use the next- generation high bandwidth memory and are designed for optimum deep learning performance.
  • The 3rd-gen AMD Infinity Architecture, which will provide a high-bandwidth, low-latency connection between the four Radeon Instinct GPUs and one AMD EPYC CPU included in each node of El Capitan. As well, the 3rd Gen AMD Infinity Architecture includes unified memory across the CPU and GPU, easing programmer access to accelerated computing.
  • An enhanced version of the open-source ROCm heterogenous programming environment, being developed to tap into the combined performance of AMD CPUs and GPUs.

“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,” says LLNL Lab Director Bill Goldstein. 

“We are pleased to partner with AMD to bring together HPE’s Cray Shasta architecture with latest AMD EPYC CPUs and Radeon Instinct GPUs and provide leadership technology in support of the mission critical HPC and AI workloads for Lawrence Livermore National Laboratory,” says Peter Ungaro, senior vice president and general manager, HPC and Mission Critical Solutions (MCS) at HPE.

“In our three U.S. exascale wins this last year, which includes the U.S. Department of Energy’s Frontier at Oak Ridge National Laboratory, the HPE systems and technologies along with AMD processors and GPUs have become a unique solution for high-performance and exascale-class computing and we look forward to continuing our collaboration to further bolster innovation,” Ungaro says.

Sources: Press materials received from the company and additional information gleaned from the company’s website.

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