R-CCS Cafe 第240回 第1部

We are developing an innovative method for computational science for sustainable promotion of scientific discovery by supercomputers in the Exascale Era by combining (Simulation + Data + Learning (S+D+L)). The Wisteria/BDEC-01 system (Big Data & Extreme Computing), which started its operation in May 2021 at the Information Technology Center, the Tokyo University, is a Hierarchical, Hybrid, Heterogeneous (h3) system, which consists of computing nodes for computational science and engineering with A64FX (Simulation Nodes) and those for data analytics/AI with NVIDIA A100 GPU’s (Data/Learning Nodes).

In this study, we consider the Wisteria/BDEC-01 as the platform for integration of (S+D+L), develop an innovative software infrastructure “h3-Open-BDEC” for integration of (S+D+L), and evaluate the effects of integration of (S+D+L) on the Wisteria/BDEC-01 system. The h3-Open-BDEC is designed for extracting the maximum performance of the supercomputers with minimum energy consumption focusing on (1) innovative method for numerical analysis with high-performance/high-reliability/power-saving based on the new principle of computing by adaptive precision, accuracy verification and automatic tuning, (2) Hierarchical Data Driven Approach (hDDA) based on machine learning, , and (3) software and utilities for heterogeneous environment, such as Wisteria/BDEC-01.
The h3-Open-BDEC is the first innovative software platform to realize integration of (S+D+L) on supercomputers in the Exascale Era, where computational scientists can achieve such integration without supports by other experts. Source codes and documents are open to public for various kinds of computational environments. This integration by h3-Open-BDEC enables significant reduction of computations and power & energy consumption, compared to those by conventional simulations.

This talk overviews the h3-Open-BDEC project, summarizes the various achievements and results of the recent progress, and provides future perspective.