Fugaku Holds Top Spot, Exascale Remains Elusive
June 28, 2021

FRANKFURT, Germany; BERKELEY, Calif.; and KNOXVILLE, Tenn.— The 57 th edition of the TOP500 saw little change in the Top10. The only new entry in the Top10 is the Perlmutter system at NERSC at the DOE Lawrence Berkeley National Laboratory. The machine is based on the HPE Cray "Shasta" platform and a heterogeneous system with both GPU-accelerated and CPU-only nodes. Perlmutter achieved 64.6 Pflop/s, putting the supercomputer at No. 5 in the new list.


TOP500 News

GREEN500: Trend of steady progress with no big step toward newer technologies.
June 28, 2021

Although there was a trend of steady progress in the Green500, nothing has indicated a big step toward newer technologies.

The system to snag the No. 1 spot for the Green500 was MN-3 from Preferred Networks in Japan. Knocked from the top of the last list by NVIDIA DGX SuperPOD in the US, MN-3 is back to reclaim its crown. This system relies on the MN-Core chip, an accelerator optimized for matrix arithmetic, as well as a Xeon Platinum 8260M processor. MN-3 achieved a 29.70 gigaflops/watt power-efficiency and has a TOP500 ranking of 337.



News Feed

Intel Announces Foundational Technology Roadmap, Launches Naming Structure for Process Nodes

Intel Corporation today announced what it said is one of the company’s most detailed process and packaging technology roadmaps, showcasing a series of “foundational innovations that will power products through 2025 and beyond.” In addition to announcing RibbonFET, its first new transistor architecture in more than a decade, and PowerVia, an industry-first new backside power […]

The post Intel Announces Foundational Technology Roadmap, Launches Naming Structure for Process Nodes appeared first on insideHPC.

Intel Sees Path Back To Chip Process Performance Leadership

For decades, Intel leaned heavily on its manufacturing prowess as a key advantage over its various competitors like AMD, which had its own chip foundry that it spun off in 2009 and which became Globalfoundries.

Intel Sees Path Back To Chip Process Performance Leadership was written by Jeffrey Burt at The Next Platform.

NVIDIA and King’s College London Use Cambridge-1 Supercomputer for Synthetic Brain Image Research

King’s College London is using the Nvidia-based Cambridge-1 supercomputer to build AI models to generate synthetic brain images by learning from tens of thousands of MRI brain scans taken of patients of various ages and with a variety of diseases. This work is intended to enable scientists to differentiate healthy brains from those that are […]

The post NVIDIA and King’s College London Use Cambridge-1 Supercomputer for Synthetic Brain Image Research appeared first on insideHPC.

DOE Computational Science Graduate Fellowship Celebrates 30 Years of Cultivating Leaders

July 26, 2021 — Since the Department of Energy’s Office for Advanced Scientific Computing Research (ASCR) and Office of Science launched the Computational Science Graduate Fellowship (DOE CSGF) in 1991, the program has supported more than 430 scientists’ training and has built a community of leaders who continue to shape this dynamic field. The program […]

The post DOE Computational Science Graduate Fellowship Celebrates 30 Years of Cultivating Leaders appeared first on HPCwire.

Will Approximation Drive Post-Moore’s Law HPC Gains?

“Hardware-based improvements are going to get more and more difficult,” said Neil Thompson, an innovation scholar at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). “I think that’s something that this crowd will probably, actually, be already familiar with.” Thompson, speaking...

The post Will Approximation Drive Post-Moore’s Law HPC Gains? appeared first on HPCwire.

Microsoft Takes Sharper Aim at On-Prem HPC

Microsoft is intent on bending the supercomputing set its direction. Instead of just focusing on competing with other public clouds, they’re aiming directly at on-prem HPC, showing comparable or better performance to existing top 10 supercomputers, for example.

Microsoft Takes Sharper Aim at On-Prem HPC was written by Nicole Hemsoth at The Next Platform.

The List

06/2021 Highlights

The only new entry in the Top10 is the Perlmutter system at NERSC at the DOE Lawrence Berkeley National Laboratory. It is based on the HPE Cray “Shasta” platform and a heterogeneous system with both GPU-accelerated and CPU-only nodes. Perlmutter achieved 64.6 Pflop/s which put it at No. 5 in the new list.

Supercomputer Fugaku, a system based on Fujitsu’s custom ARM A64FX processor remains No. 1. It is installed at the RIKEN Center for Computational Science (R-CCS) in Kobe, Japan, the location of the former K-Computer. It was co-developed in close partnership by Riken and Fujitsu and uses Fujitsu’s Tofu D interconnect to transfer data between nodes. Its HPL benchmark score to 442 Pflop/s easily exceeding the No. 2 Summit by 3x. In single or further reduced precision, which are often used in machine learning and AI applications, it’s peak performance is actually above 1,000 PFlop/s (= 1 Exaflop/s) and because of this, it is often introduced as the first ‘Exascale’ supercomputer. Fugaku actually already demonstrated this new level of performance on the new HPL-AI benchmark with 2 Exaflops! https://www.r-ccs.riken.jp/en/

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