Large-scale, high-speed tsunami prediction for the Great Nankai Trough Earthquake on the K computer. (February 2016)

• Record Type: Journal Article
• Authors: Baba, Toshitaka; Ando, Kazuto; Matsuoka, Daisuke; Hyodo, Mamoru; Hori, Takane; Takahashi, Narumi; Obayashi, Ryoko; Imato, Yoshiyuki; Kitamura, Dai; Uehara, Hitoshi; Kato, Toshihiro; Saka, Ryotaro
• Is Part Of: International journal of high performance computing applications. Volume 30:Number 1(2016:Spring)
• Page Start: 71
• Page End: 84
• Publication Date: 2016-02
• Subjects: Tsunami prediction -- parallel scalability -- K computer -- JAGURS -- Nankai trough; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342015584090
• Languages: English
• ISSNs: 1094-3420

Abstract

We improved the tsunami simulation code JAGURS, which is a paralleled version of URSGA code for a large-scale, high-speed tsunami prediction in the Nankai trough, Japan. We optimized the loop kernel for velocity update and intergrid communication on a three-dimensional torus network. Linear scaling was achieved up to the full system capability of the K computer (82, 944 nodes) in a strong scaling test that used 100 billion finite-difference grid points. The measured performance on the K computer was 1.2 petaflops (11.5% of peak speed). Intergrid communication was optimized for a three-nested-grid model consisting of 0.68 billion grid points. Grid spacing in the area with the finest grid (180 km × 120 km) was about 5 m. We successfully implemented a large-scale tsunami simulation using this model that ran in about 30% of real time. We believe that this is the fastest tsunami prediction achieved to date with such a large-scale model. Our code can provide high-resolution tsunami prediction for broad regions within a reasonable time to assist emergency rescue and relief operations during future devastating tsunamis comparable to the 2004 Sumatra, 2010 Chile, and 2011 Tohoku tsunamis.