[A-AS08] Weather, Climate, and Environmental Science Studies using High-Performance Computing

[AAS08-01] Innovative Supercomputing by Integration of Simulation/Data/Learning

★Invited Papers

*Kengo Nakajima¹ (1.Information Technology Center, The University of Tokyo)

Keywords:Supercomputing, Data Analytics, Machine Learning/AI

Supercomputing is shifting from the traditional simulation for computational science to the integration with data science and machine learning. Since 2015, the Information Technology Center, the University of Tokyo (ITC/U.Tokyo) has been working on the “Big Data & Extreme Computing (BDEC)” project aimed at new supercomputing through the integration of “Simulation/Data/Learning (S+D+L)”. In May 2021, Wisteria/BDEC-01, the first system of the BDEC project, began its operation. Wisteria/BDEC-01 has a total peak performance of 33+PF, and consists of a simulation node group (Odyssey) consisting of 7,680x A64FX nodes and a data/learning node group (Aquarius) equipped with 360x NVIDIA A100 GPUs. . Aquarius can be directly connected to the outside and real-time acquisition of observation data is also possible. Some nodes of Aquarius are directly connected to the outside, and real-time acquisition of observation data etc. is also possible via SINET. Since 2019, we have been developing an innovative software platform "h3-Open-BDEC" that realizes the integration of (S+D+L).), with the support of Grant-in-Aid for Scientific Research (S). Integration of (S+D+L) is now being realized on Wisteria/BDEC-01. In this lecture, I will introduce these activities and introduce "OFP-II", which is being introduced at the Joint Center for Advanced High Performance Computing (JCAHPC) in collaboration with University of Tsukuba, aiming to start operation in 2024. Finally, I will talk about the outlook for supercomputing ten years from now.