The expansion of AI technology affects not only the production and demand for graphics cards but also the electricity grid that powers them. Data centers hosting thousands of GPUs are becoming more common, and the industry has been building new facilities for GPU-enhanced servers to serve the need for more AI. However, these powerful GPUs often consume over 500 Watts per single card, and NVIDIA's latest Blackwell B200 GPU has a TGP of 1000 Watts or a single kilowatt. These kilowatt GPUs will be present in data centers with 10s of thousands of cards, resulting in multi-megawatt facilities. To combat the load on the national electricity grid, US President Joe Biden's administration has been discussing with big tech to re-evaluate their power sources, possibly using smaller nuclear plants. According to an Axios interview with Energy Secretary Jennifer Granholm, she has noted that "AI itself isn't a problem because AI could help to solve the problem." However, the problem is the load-bearing of the national electricity grid, which can't sustain the rapid expansion of the AI data centers.

The Department of Energy (DOE) has been reportedly talking with firms, most notably hyperscalers like Microsoft, Google, and Amazon, to start considering nuclear fusion and fission power plants to satisfy the need for AI expansion. We have already discussed the plan by Microsoft to embed a nuclear reactor near its data center facility and help manage the load of thousands of GPUs running AI training/inference. However, this time, it is not just Microsoft. Other tech giants are reportedly thinking about nuclear as well. They all need to offload their AI expansion from the US national power grid and develop a nuclear solution. Nuclear power is a mere 20% of the US power sourcing, and DOE is currently financing a Holtec Palisades 800-MW electric nuclear generating station with $1.52 billion in funds for restoration and resumption of service. Microsoft is investing in a Small Modular Reactors (SMRs) microreactor energy strategy, which could be an example for other big tech companies to follow.

Increasing its HPL score from 1.02 Eflop/s in November 2022 to an impressive 1.194 Eflop/s on this list, Frontier was able to improve upon its score after a stagnation between June 2022 and November 2022. Considering exascale was only a goal to aspire to just a few years ago, a roughly 17% increase here is an enormous success. Additionally, Frontier earned a score of 9.95 Eflop/s on the HLP-MxP benchmark, which measures performance for mixed-precision calculation. This is also an increase over the 7.94 EFlop/s that the system achieved on the previous list and nearly 10 times more powerful than the machine's HPL score. Frontier is based on the HPE Cray EX235a architecture and utilizes AMD EPYC 64C 2 GHz processors. It also has 8,699,904 cores and an incredible energy efficiency rating of 52.59 Gflops/watt. It also relies on gigabit ethernet for data transfer.

The 60th edition of the TOP500 reveals that the Frontier system is still the only true exascale machine on the list.

With an HPL score of 1.102 EFlop/s, the Frontier machine at Oak Ridge National Laboratory (ORNL) did not improve upon the score it reached on the June 2022 list. That said, Frontier's near-tripling of the HPL score received by second-place winner is still a major victory for computer science. On top of that, Frontier demonstrated a score of 7.94 EFlop/s on the HPL-MxP benchmark, which measures performance for mixed-precision calculation. Frontier is based on the HPE Cray EX235a architecture and it relies on AMD EPYC 64C 2 GHz processor. The system has 8,730,112 cores and a power efficiency rating of 52.23 gigaflops/watt. It also relies on gigabit ethernet for data transfer.

Tachyum today announced that it has responded to a U.S. Department of Energy Request for Information soliciting Advanced Computing Ecosystems for DOE national laboratories engaged in scientific and national security research. Tachyum has submitted a proposal to create a 20-exaflop supercomputer based on Tachyum's Prodigy, the world's first universal processor.

The DOE's request calls for computing systems that are five to 10 times faster than those currently available and/or that can perform more complex applications in "data science, artificial intelligence, edge deployments at facilities, and science ecosystem problems, in addition to the traditional modeling and simulation applications."

The National Renewable Energy Laboratory (NREL) has selected Hewlett Packard Enterprise (HPE) to build its third-generation, high performance computing (HPC) system, called Kestrel. Named for a falcon with keen eyesight and intelligence, Kestrel's moniker is apropos for its mission—to rapidly advance the U.S. Department of Energy's (DOE's) energy research and development (R&D) efforts to deliver transformative energy solutions to the entire United States.

Installation of the new system will begin in the fall of 2022 in NREL's Energy Systems Integration Facility (ESIF) data center. Kestrel will complement the laboratory's current supercomputer, Eagle, during the transition. When completed—in early 2023—Kestrel will accelerate energy efficiency and renewable energy research at a pace and scale more than five times greater than Eagle, with approximately 44 petaflops of computing power.

The U.S. Department of Energy's (DOE's) National Nuclear Security Administration (NNSA) selected next-generation Intel Xeon Scalable processors (code-named "Sapphire Rapids") to power the supercomputers used within NNSA's Life Extension Program for mission-critical efforts in stockpile stewardship. The NNSA's Lawrence Livermore National Laboratory awarded a subcontract to Dell Technologies to supply the Intel-powered computing systems that will be deployed at the NNSA's Tri-Labs (Lawrence Livermore National Laboratory, Los Alamos National Laboratory and Sandia National Laboratories).

Today's news supports the NNSA's Advanced Simulation and Computing (ASC) program operated at the NNSA's Tri-Labs. The Commodity Technology Systems contract (CTS-2) awarded today will enable these three national laboratories to build more powerful, energy-efficient computing systems that will focus on performing extensive modeling and simulation capabilities in support of NNSA's stockpile stewardship program.

Los Alamos National Laboratory has completed the installation of a next-generation high performance computing platform, with aim to enhance its ongoing R&D efforts in support of the nation's response to COVID-19. Named Chicoma, the new platform is poised to demonstrate Hewlett Packard Enterprise's new HPE Cray EX supercomputer architecture for solving complex scientific problems.

"As extensive social and economic impacts from COVID-19 continue to grip the nation, Los Alamos scientists are actively engaged in a number of critical research efforts ranging from therapeutics design to epidemiological modeling," said Irene Qualters, Associate Laboratory Director for Simulation and Computing at Los Alamos. "High Performance Computing is playing a critical role by allowing scientists to model the complex phenomena involved in viral evolution and propagation."

The National Energy Research Scientific Computing Center (NERSC), the mission high-performance computing facility for the U.S. Department of Energy's Office of Science, has moved another step closer to making Perlmutter - its next-generation GPU-accelerated supercomputer - available to the science community in 2020.

In mid-April, NERSC finalized its contract with Cray - which was acquired by Hewlett Packard Enterprise (HPE) in September 2019 - for the new system, a Cray Shasta supercomputer that will feature 24 cabinets and provide 3-4 times the capability of NERSC's current supercomputer, Cori. Perlmutter will be deployed at NERSC in two phases: the first set of 12 cabinets, featuring GPU-accelerated nodes, will arrive in late 2020; the second set, featuring CPU-only nodes, will arrive in mid-2021. A 35-petabyte all-flash Lustre-based file system using HPE's ClusterStor E1000 hardware will also be deployed in late 2020.

AMD has been on a roll in both consumer, professional, and exascale computing environments, and it has just snagged itself another hugely important contract. The US Department of Energy (DOE) has just announced the winners for their next-gen, exascale supercomputer that aims to be the world's fastest. Dubbed "El Capitan", the new supercomputer will be powered by AMD's next-gen EPYC Genoa processors (Zen 4 architecture) and Radeon GPUs. This is the first such exascale contract where AMD is the sole purveyor of both CPUs and GPUs, with AMD's other design win with EPYC in the Cray Shasta being paired with NVIDIA graphics cards.

El Capitan will be a $600 million investment to be deployed in late 2022 and operational in 2023. Undoubtedly, next-gen proposals from AMD, Intel and NVIDIA were presented, with AMD winning the shootout in a big way. While initially the DOE projected El Capitan to provide some 1.5 exaflops of computing power, it has now revised their performance goals to a pure 2 exaflop machine. El Capitan willl thus be ten times faster than the current leader of the supercomputing world, Summit.

Global supercomputer leader Cray, a Hewlett Packard Enterprise company, and leading Japanese information and communication technology company Fujitsu, today announced a partnership to offer high performance technologies for the Exascale Era. Under the alliance agreement, Cray is developing the first-ever commercial supercomputer powered by the Fujitsu A64FX Arm -based processor with high-memory bandwidth (HBM) and supported on the proven Cray CS500 supercomputer architecture and programming environment. Initial customers include Los Alamos National Laboratory, Oak Ridge National Laboratory, RIKEN Center for Computational Science, Stony Brook University, and University of Bristol. As part of this new partnership, Cray and Fujitsu will explore engineering collaboration, co-development, and joint go-to-market to meet customer demand in the supercomputing space.

"Our partnership with Fujitsu means customers now have a broader choice of processor technology to address their pressing computational needs," said Fred Kohout, senior vice president and CMO at Cray, a Hewlett Packard Enterprise company. "We are delivering the development-to-deployment experience customers have come to expect from Cray, including exploratory development to the Cray Programming Environment (CPE) for Arm processors to optimize performance and scalability with additional support for Scalable Vector Extensions and high bandwidth memory."

Developing supercomputers isn't for the faint of heart. Much less it is for those that are looking for fast development and deployment time-frames. And as such, even as the world's supercomputers are getting increasingly faster and exorbitantly expensive to develop and deploy, players who want to stay ahead have to think ahead as well. To this end, the US Department of Energy has awarded a total of $258M in research contracts to six of the US's foremost tech companies to accelerate the development of Exascale Supercomputer technologies (AMD, Cray, Hewlett Packard Enterprise, IBM, Intel, and NVIDIA.) These companies will be working over a three year contract period, and will have to support at least 40% of the project cost - to help develop the technologies needed to build an exascale computer for 2021. It isn't strange that the companies accepted the grant and jumped at the opportunity: 60% savings in research and development they'd have to do for themselves is nothing to scoff at.

Supercomputers birthed from the project are expected to be in the exaFLOPS scale of computing performance, which is around 50 times more processing power than the generation of supercomputers being installed now. Since traditional supercomputing knowledge and materials are known to falter at the objective level of exaFLOPS performance, the PathForward program - which looks to ensure achievement of such systems in a timely fashion to ensure US leadership in the field of supercomputing - will need to see spurred research and development, which the $258M grant is looking out to do.