摘要
格子玻尔兹曼方法(Lattice Boltzmann Method,LBM)是一种基于介观模拟尺度的计算流体力学方法,已被广泛用于理论研究和工程领域。提高LBM计算流体软件的并行模拟能力,是高性能计算及应用研究中的一项重要内容。该研究基于“神威·太湖之光”超级计算系统,设计并实现了一套高效扩展的LBM计算流体力学软件。针对国产众核处理器SW26010的架构,文中设计了以下几种提高SWLBM方针速度和可扩展性的多级并行技术,包括面向19点stencil的数据复用、碰撞过程向量化、主从异步并行通信计算隐藏等。基于以上并行优化方案,文中测试了高达56000亿网格的数值模拟,SWLBM软件持续浮点计算性能达到4.7 PFlops,软件模拟速度提高了172倍。相比百万核心10000*10000*5000网格风场模拟,SWLBM整机千万核心的并行效率可达87%。测试结果表明,SWLBM有能力为工业应用提供实用的大规模并行模拟解决方案。
Lattice Boltzmann Method(LBM)is a computational fluid dynamics method based on mesoscopic simulation scales and has been widely used in theoretical research and processing engineering problems.Improving the parallel simulation capability of LBM Computing Fluid software is an important study for high performance computing and applications.The research aims to design and implement a set of highly efficient extended LBM computational fluid dynamics software based on the“Sunway TaihuLight”supercomputing system.According to the architecture of domestic multi-core processor SW26010,several parallel optimization multi-level parallelism techniques to boost the simulation speed and improve the scalability of SWLBM are designed,including date reuse of 19-point stencil,vectorization of collision process and communication overlap computing.Based on these parallel optimization schemes,the numerical simulation with over 10 million cores and up to 5.6 trillion grids is tested and the SWLBM software can bring up to 172x speed up and achieve a sustained floating of 4.7 PFlops.Compared with the million-core 10000*10000*5000 grid wind filed simulation,the SWLBM machine has a core efficiency of 87%.Test results show that SWLBM has the ability to provide practical large-scale parallel simulation solutions for industrial applications.
作者
吕小敬
刘钊
褚学森
石树鹏
孟虹松
黄震春
LV Xiao-jing;LIU Zhao;CHU Xue-sen;SHI Shu-peng;MENG Hong-song;HUANG Zhen-chun(National Supercomputing Center in Wuxi,Wuxi,Jiangsu 214072,China;Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China;China Ship Scientific Research Center,Wuxi,Jiangsu 214072,China)
出处
《计算机科学》
CSCD
北大核心
2020年第4期13-17,共5页
Computer Science
基金
国家重点研发计划(2017YFB0203602)。