World’s fastest supercomputer is still Frontier, 2.5X faster than #2

World’s fastest supercomputer is still Frontier, 2.5X faster than #2

The top 10 of the semiannual TOP500 list of supercomputers for November 2022 has just one new entrant, Leonardo, which jumped in at #4.

Credit: Dreamstime

Frontier, which became the first exascale supercomputer in June and ranked number one among the fastest in the world, retained that title in the new TOP500 semiannual list of the world’s fastest.

Without any increase in its speed — 1.102EFLOP/s — Frontier still managed to score 2.5 times faster that the number two finisher, Fugaku, which also came in second in the June rankings. An exascale computer is one that can perform 1018 (one quintillion) floating point operations per second (1 exaFLOP/s).

Despite doubling its maximum speed since it was ranked number three in June, the Lumi supercomputer remained in third-place.

There was just one new member of the top-ten list, and that was Leonardo, which came in fourth after finishing a distant 150th in the TOP500 rankings in June.

In addition to ranking number one for flat-out speed, Frontier also ranked as the supercomputer ranking highest in a test of its suitability for doing artificial intelligence (AI) functions, a classification known as HPL-MxP. The pure speed measurement is known as the High Performance Linpack (HPL) benchmark, which measures how well systems solve a dense system of linear equations.

Here are the top ten on the November 2022 TOP500 list:


An HPE Cray EX system run by the US Department of Energy, Frontier incorporates 3rd Gen AMD EPYC™ CPUs representing 8,730,112 cores that have been optimised for high-performance computing (HPC) and AI with AMD Instinct™ 250X accelerators and Slingshot-11 interconnects. Its HPL benchmark was 1.102EFLOP/s.


Supercomputer Fugaku, housed at the RIKEN Centre for Computational Science in Kobe, Japan, scored 442.01PFLOP/s in the HPL test. It is built on the Fujitsu A64FX microprocessor and has 7,630,848 cores.


LUMI is an HPE Cray EX system at the EuroHPC centre at CSC in Kajaani, Finland, with a performance of 151.9 PFLOP/s. It relies on AMD processors and boasts 2,220,288 cores.


Leonardo, which resides in Bolbogna, Italy, is an Intel/Nvidia system with 1,463,616 cores and a maximum speed of 174.70PFLOP/s.


An IBM system at Oak Ridge National Laboratory in Tennessee, Summit scored 148.8 PFLOP/s on the HPL benchmark. It has 4,356 nodes, each with two Power9 CPUs with 22 cores and six Nvidia Tesla V100 GPUs, each with 80 streaming multiprocessors (SM). The nodes are linked by a Mellanox dual-rail EDR InfiniBand network. It has 2,414,592 cores.


Similar in architecture to Summit, Sierra reached 94.6 PFLOP/s. It has 4,320 nodes with two Power9 CPUs and four Nvidia Tesla V100 GPUs and a total of 1,572,480 cores. It is housed at the Lawrence Livermore National Laboratory, in California.

#7—Sunway TaihuLight

Sunway TaihuLight is a machine developed by National Research Centre of Parallel Computer Engineering & Technology (NRCPC) in China and is installed in the city of Wuxi. It reached 93PFLOP/s on the HPL benchmark. It has 10,649,600 cores.


The Perlmutter system is based on the HPE Cray Shasta platform and is a heterogeneous system with both AMD EPYC-based nodes and 1536 Nvidia A100-accelerated nodes. It has 761,856 cores. It achieved 70.87 PFLOP/s. That’s an improvement of about 6PFLOP/s over last year’s score, but still not enough to catch Sunway TaihuLight.


Selene is an Nvidia DGX A100 SuperPOD based on an AMD EPYC processor with Nvidia A100s for acceleration and a Mellanox HDR InfiniBand as a network. It has 555,520 cores. It achieved 63.4 PFLOP/s and is installed in-house at Nvidia facilities in the US.

#10—Tianhe-2A (Milky Way-2A)

Powered by Intel Xeon CPUs and NUDT’s Matrix-2000 DSP accelerators, Tianhe-2A has 4,981,760 cores in the system to achieve 61.4 Pflop/s. It was developed by China’s National University of Defense Technology (NUDT) and is deployed at the National Supercomputer Centre in Guangzhou, China.

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