Performance Evaluation of Tsunami Inundation Simulation on SX-Aurora TSUBASA

Akihiro Musa, Takashi Abe, Takumi Kishitani, Takuya Inoue, Masayuki Sato, Kazuhiko Komatsu, Yoichi Murashima, Shunichi Koshimura, Hiroaki Kobayashi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


As tsunamis may cause damage in wide area, it is difficult to immediately understand the whole damage. To quickly estimate the damages of and respond to the disaster, we have developed a real-time tsunami inundation forecast system that utilizes the vector supercomputer SX-ACE for simulating tsunami inundation phenomena. The forecast system can complete a tsunami inundation and damage forecast for the southwestern part of the Pacific coast of Japan at the level of a 30-m grid size in less than 30 min. The forecast system requires higher-performance supercomputers to increase resolutions and expand forecast areas. In this paper, we compare the performance of the tsunami inundation simulation on SX-Aurora TSUBASA, which is a new vector supercomputer released in 2018, with those on Xeon Gold and SX-ACE. We clarify that SX-Aurora TSUBASA achieves the highest performance among the three systems and has a high potential for increasing resolutions as well as expanding forecast areas.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2019 - 19th International Conference, Proceedings
EditorsJoão M.F. Rodrigues, Pedro J.S. Cardoso, Jânio Monteiro, Roberto Lam, Valeria V. Krzhizhanovskaya, Michael H. Lees, Peter M.A. Sloot, Jack J. Dongarra
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783030227401
Publication statusPublished - 2019
Event19th International Conference on Computational Science, ICCS 2019 - Faro, Portugal
Duration: 2019 Jun 122019 Jun 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11537 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Computational Science, ICCS 2019


  • Supercomputer
  • System performance
  • Tsunami simulation


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