Academic Thesis

Basic information

Name Kido Yoshiyuki
Belonging department
Occupation name
researchmap researcher code B000242986
researchmap agency Okayama University of Science

Title

A real-time Tsunami inundation forecast system using vector supercomputer SX-ACE

Bibliography Type

 

Author

Akihiro Musa
Akihiro Musa
Takashi Abe
Takuya Inoue
Takuya Inoue
Takuya Inoue
Hiroaki Hokari
Yoichi Murashima
Yoichi Murashima
Yoichi Murashima
Yoshiyuki Kido
Susumu Date
Shinji Shimojo
Shunichi Koshimura
Hiroaki Kobayashi

Summary

© 2018, Fuji Technology Press. All rights reserved. Tsunami disasters can cause serious casualties and damage to social infrastructures. An early understanding of disaster states is required in order to advise evacuations and plan rescues and recoveries. We have developed a real-time tsunami inundation forecast system using a vector supercomputer SX-ACE. The system can complete a tsunami inundation and damage estimation for coastal city regions at the resolution of a 10 m grid size in under 20 minutes, and distribute tsunami inundation and infrastructure damage information to local governments in Japan. We also develop a new configuration for the computational domain, which is changed from rectangles to polygons and called a polygonal domain, in order to effectively simulate in the entire coast of Japan. Meanwhile, new supercomputers have been developed, and their peak performances have increased year by year. In 2016, a new Xeon Phi processor called Knights Landing was released for high-performance computing. In this paper, we present an overview of our real-time tsunami inundation forecast system and the polygonal domain, which can decrease the amount of computation in a simulation, and then discuss its performance on a vector supercomputer SX-ACE and a supercomputer system based on Intel Xeon Phi. We also clarify that the real-time tsunami inundation forecast system requires the efficient vector processing of a supercomputer with high-performance cores.

Magazine(name)

Journal of Disaster Research

Publisher

 

Volume

13

Number Of Pages

2

StartingPage

234

EndingPage

244

Date of Issue

2018-02

Referee

Exist

Invited

Not exist

Language

English

Thesis Type

Research papers (academic journals)

ISSN

 

DOI

10.20965/jdr.2018.p0234

NAID

 

PMID

 

J-GLOBAL ID

 

arXiv ID

 

ORCID Put Code

 

DBLP ID