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Fujitsu has today officially completed the delivery of the Fugaku supercomputer to the Riken scientific research institute of Japan. This is a big accomplishment as the current COVID-19 pandemic has delayed many happenings in the industry. However, Fujitsu managed to play around that and deliver the supercomputer on time. The last of 400 racks needed for the Fugaku supercomputer was delivered today, on May 13th, as it was originally planned. The supercomputer is supposed to be fully operational starting on the physical year of 2021, where the installation and setup will be done before.
As a reminder, the Fugaku is an Arm-based supercomputer consisting out of 150 thousand A64FX CPUs. These CPUs are custom made processors by Fujitsu based on Arm v8.2 ISA, and they feature 48 cores built on TSMC 7 nm node and running above 2 GHz. Packing 8.786 billion transistors, this monster chips use HBM2 memory instead of a regular DDR memory interface. Recently, a prototype of the Fugaku supercomputer was submitted to the Top500 supercomputer list and it came on top for being the most energy-efficient of all, meaning that it will be as energy efficient as it will be fast. Speculations are that it will have around 400 PetaFlops of general compute power for Dual-Precision workloads, however, for the specific artificial intelligence applications, it should achieve ExaFLOP performance target.
View at TechPowerUp Main Site
As a reminder, the Fugaku is an Arm-based supercomputer consisting out of 150 thousand A64FX CPUs. These CPUs are custom made processors by Fujitsu based on Arm v8.2 ISA, and they feature 48 cores built on TSMC 7 nm node and running above 2 GHz. Packing 8.786 billion transistors, this monster chips use HBM2 memory instead of a regular DDR memory interface. Recently, a prototype of the Fugaku supercomputer was submitted to the Top500 supercomputer list and it came on top for being the most energy-efficient of all, meaning that it will be as energy efficient as it will be fast. Speculations are that it will have around 400 PetaFlops of general compute power for Dual-Precision workloads, however, for the specific artificial intelligence applications, it should achieve ExaFLOP performance target.
View at TechPowerUp Main Site
