Communication Reduced Multi-time-step Algorithm for Real-time Wind Simulation on GPU-based Supercomputers

被引：9

作者：

Onodera, Naoyuki ^{[1
]}

Idomura, Yasuhiro ^{[1
]}

Ali, Yussuf ^{[1
]}

Shimokawabe, Takashi ^{[2
]}

机构：

[1] Japan Atom Energy Agcy, Kashiwa, Chiba, Japan

[2] Univ Tokyo, Bunkyo Ku, Tokyo, Japan

来源：

SCALA 2018: PROCEEDINGS OF 2018 IEEE/ACM 9TH WORKSHOP ON LATEST ADVANCES IN SCALABLE ALGORITHMS FOR LARGE-SCALE SYSTEMS (SCALA) | 2018年

基金：

日本学术振兴会;

关键词：

Locally Mesh Refinement; Communication Reduced Multi-time-step Algorithm; GPU; Wind Simulation; LATTICE BOLTZMANN METHOD; ADAPTIVE MESH REFINEMENT; GRID-REFINEMENT; TURBULENT FLOWS;

D O I：

10.1109/ScalA.2018.00005

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We develop a communication reduced multi-timestep (CRMT) algorithm for a Lattice Boltzmann method (LBM) based on a block-structured adaptive mesh refinement (AMR). This algorithm is based on the temporal blocking method, and can improve computational efficiency by replacing a communication bottleneck with additional computation. The proposed method is implemented on an extreme scale airflow simulation code CityLBM, and its impact on the scalability is tested on GPU based supercomputers, TSUBAME and Reedbush. Thanks to the CRMT algorithm, the communication cost is reduced by similar to 64%, and weak and strong scalings are improved up to similar to 200 GPUs. The obtained performance indicates that real time airflow simulations for about 2km square area with the wind speed of similar to 5m/s is feasible using 1m resolution.

引用

页码：9 / 16

页数：8

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