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El Capitan Supercomputer : AMD Selected As Node Supplier!

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It’s official – AMD has been selected as the node supplier for the El Capitan supercomputer, which is projected to be the world’s most powerful supercomputer when it is fully deployed!

 

El Capitan Supercomputer : A Quick Primer!

El Capitan is a supercomputer funded by the Advanced Simulation and Computing (ASC) program at the National Nuclear Security Administration (NNSA) from the Department of Energy.

When it is fully deployed in 2023, it will perform complex and increasingly predictive modelling and simulation for the NNSA’s Life Extension Programs (LEPs), which addresses nuclear weapon raging and emergent threat issues.

This will allow the United States to keep its nuclear stockpile safe, secure and reliable, in the absence of underground nuclear testing.

“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.

“Today’s news provides a prime example of how government and industry can work together for the benefit of the entire nation.”

Besides supporting the nuclear stockpile, El Capitan will perform secondary US national security missions, including nuclear nonproliferation and counterterrorism.

NNSA laboratories – Lawrence Livermore, Los Alamos and Sandia national laboratories – are building machine learning and AI into computational techniques and analysis that will benefit NNSA’s primary missions and unclassified projects such as climate modelling and cancer research for DOE.

To that end, it will use a combination of CPUs and GPUs to exceed 2 exaFLOPS in performance – that’s two quintillion floating point operations per second. That will make it the world’s most powerful supercomputer!

 

El Capitan Supercomputer : AMD Selected As Node Supplier!

El Capitan will be powered by the next-generation AMD EPYC processors, codenamed Genoa and featuring the upcoming AMD Zen 4 processor cores, as well as the next-generation AMD Radeon Instinct GPUs based on a new compute-optimised architecture.

The nodes will run on the AMD Radeon Open Compute (ROCm) heterogenous computing platform, with most of their floating point computing power delivered by the Radeon Instinct GPUs.

Not only will the El Capitan nodes offer significantly greater per-node performance than any current system, they will also offer dramatically better energy efficiency.

El Capitan will also integrated advanced features that have not yet been widely deployed, including :

  • HPE Cray Slingshot interconnect network, which will enable large calculations across many nodes
  • new HPE optics technologies to deliver higher data transmission rates with better power efficiency and reliability
  • new Cray Shasta software platform, with a new container-based architecture

“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.

“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.”

“We are extremely proud to continue our exascale work with HPE and NNSA and look forward to the delivery of the most powerful supercomputer in the world, expected in early 2023.”

 

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NVIDIA Among 6 Companies In Exascale Computing Project

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June 16, 2017 — NVIDIA is among six technology companies to receive funding from the U.S. Department of Energy’s Exascale Computing Project (ECP) to accelerate the development of next-generation supercomputers.

 

The Exascale Computing Project

The ECP mission is to facilitate the delivery of at least two exascale computing systems, with an aim to deliver at least one by 2021. Such systems would be approximately 50x more powerful than the nation’s fastest supercomputer, Titan, located at Oak Ridge National Laboratory, in use today.

The goal of the ECP PathForward programme is to find solutions that maximise the energy efficiency and overall performance of future large-scale supercomputers critical to areas such as national security, manufacturing, industrial competitiveness, and energy research.

In addition to performance, the DOE has ambitious goals for improving power efficiency, to achieve exascale performance using only 20-30 megawatts. By comparison, an exascale system built with CPUs alone could consume hundreds of megawatts.

 

NVIDIA In The Exascale Computing Project

NVIDIA has been researching and developing faster, more efficient GPUs for high performance computing for more than a decade. This is its sixth DOE research and development subcontract, which will help accelerate its efforts to develop highly efficient throughput computing technologies to ensure U.S. leadership in HPC.

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NVIDIA’s R&D will focus on critical areas including energy-efficient GPU architectures and resilience. Its findings may be incorporated into future generation GPU architectures after Volta (which will be used in the DOE’s upcoming flagship Summit and Sierra supercomputers, scheduled to go online in 2018).

The DOE has placed a high priority on supercomputer research. Its PathForward technical requirements state, “The U.S. faces serious and urgent economic, environmental, and national security challenges based on energy, climate, and growing security threats. High performance computing is a requirement for addressing such challenges, and the need for the development of capable exascale computers has become critical for solving these problems.”

To facilitate and test its technology, NVIDIA research teams will collaborate closely with six national DOE laboratories: Argonne National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories.

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