Japan Geoscience Union Meeting 2018

Presentation information

[JJ] Evening Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI28] Development of computational sciences on planetary formation, evolution and surface environment

Wed. May 23, 2018 5:15 PM - 6:30 PM Poster Hall (International Exhibition Hall7, Makuhari Messe)

convener:Yoshi-Yuki Hayashi(Department of Planetology/CPS, Graduate School of Science, Kobe University), Masaki Ogawa(Division of General Systems Studies, Graduate School of Arts and Sciences, University of Tokyo), Shigeru Ida(東京工業大学地球生命研究所, 共同), Kanya Kusano(Institute for Space-Earth Environmental Research, Nagoya University)

[MGI28-P02] Speed-up efficiencies of an SPH code with FDPS on GPUs or PEZY-SCs

*Natsuki Hosono1,2, Masaki Iwasawa2, Daisuke Namekata2, Ataru Tanikawa3,2, Keigo Nitadori2, Takayuki Muranushi2, Junichiro Makino4,2 (1.Japan Agency for Marine-Earth Science and Technology, 2.Advanced Institute for Computational Science, RIKEN, 3.The University of Tokyo, 4.Kobe University)

Keywords:numerical hydrodynamics

Since the many important phenomena in planetary science are difficult to study by means of laboratory experiments, numerical simulations play an important role.
Smoothed Particle Hydrodynamics (SPH) is a widely used particle-based numerical hydrodynamic simulation method, which has advantages to deal with large deformation, multi-component and self-gravity.
Since the reliability of SPH depends on the number of particles used in each run, high-performance computing can be an important topic.
However, compared to mesh-based methods, it requires relatively high computational costs.
We have developed a framework, Framework for Developing Particle Simulator (FDPS) which automatically parallelise an arbitrary particle-based numerical code.
Thus, recently, it has been popular to apply so-called ``accelerator'', such as GPUs, to SPH.
Combining these two techniques, we have developed a massively parallel SPH code which works on either GPUs or PEZY-SCs.
We will report the speed-up efficiency of our code.