Performance Evaluation of Tsunami Inundation Simulation on SX-Aurora TSUBASA

  • Akihiro MusaEmail author
  • Takashi Abe
  • Takumi Kishitani
  • Takuya Inoue
  • Masayuki Sato
  • Kazuhiko Komatsu
  • Yoichi Murashima
  • Shunichi Koshimura
  • Hiroaki Kobayashi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11537)


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.


System performance Supercomputer Tsunami simulation 



The authors would like to thank Mr. Takayuki Suzuki and Mr. Atsushi Tanobe of Kokusai Kogyo Co., LTD. for developing the tsunami model. This study was partially supported by JSPS KAKENHI Grant Numbers 16K12845, 17H06108, 18K11322, JST CREST Grant Number JP-MJCR1411, Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures in Japan (Project ID: jh180040-NAH), and Ministry of Education, Culture, Sports, Science and Technology of Japan (Next Generation High-Performance Computing Infrastructures and Applications R&D Program). In this work, we used SX-ACE of the Cyberscience Center at Tohoku University, and SX-ACE and Octopus of the Cybermedia Center at the Osaka University.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Akihiro Musa
    • 1
    • 2
    Email author
  • Takashi Abe
    • 1
  • Takumi Kishitani
    • 1
  • Takuya Inoue
    • 1
    • 3
  • Masayuki Sato
    • 1
  • Kazuhiko Komatsu
    • 1
  • Yoichi Murashima
    • 1
    • 3
  • Shunichi Koshimura
    • 1
  • Hiroaki Kobayashi
    • 1
  1. 1.Tohoku UniversitySendaiJapan
  2. 2.NEC CorporationTokyoJapan
  3. 3.Kokusai Kogyo Co., LTD.Fuchu-shi, TokyoJapan

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