2023 Fiscal Year Annual Research Report

ExaPath: Hierarchical Routing for Next-Gen Supercomputers and Beyond

Research Project

Project/Area Number	19H04119
Research Institution	Institute of Physical and Chemical Research
Principal Investigator	ドンケイェンス国立研究開発法人理化学研究所, 計算科学研究センター, チームリーダー (70815480)
Co-Investigator(Kenkyū-buntansha)	遠藤敏夫東京工業大学, 学術国際情報センター, 教授 (80396788)
Project Period (FY)	2019-04-01 – 2024-03-31
Keywords	HPC interconnects
Outline of Annual Research Achievements	In FY23, we continued with MocCUDA approach to speedup the large scale execution of deep learning frameworks on Fugaku. Additonally, we hosted an intern from ETH Zurich, with whom we published in the high-ranked NSDI'24 conference: "A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network", a continuation of our routing work specifically tailored for SimFly networks. Furthermore, we established a collaboration with Univ. of Illinois at Chicago, and our work on co-designing a better Alltoallv for GraphNN and FFT is under review at ICPP. Lastly, together with ETH we designed a holistic toolchain, called EvalNet, which can simulate large-scale networks. The tool performs topology generation, routing, path analysis, and metric evaluation at various scales.
Research Progress Status	令和5年度が最終年度であるため、記入しない。
Strategy for Future Research Activity	令和5年度が最終年度であるため、記入しない。