A Peta-scalable CPU-GPU Algorithm for Global Atmospheric Simulations

	A Peta-scalable CPU-GPU Algorithm for Global Atmospheric Simulations
	Yang, Chao; Xue, Wei; Fu, Haohuan; Gan, Lin; Li, Linfeng; Xu, Yangtong; Lu, Yutong; Sun, Jiachang; Yang, Guangwen; Zheng, Weimin
刊名	ACM SIGPLAN NOTICES
	2013
卷号	48 期号:8 页码:1-11
关键词	parallel algorithm atmospheric modeling GPU heterogeneous system communication-computation overlap scalability
ISSN号	0362-1340
通讯作者	Yang, C (reprint author), Chinese Acad Sci, Inst Software, Beijing, Peoples R China.
英文摘要	Developing highly scalable algorithms for global atmospheric modeling is becoming increasingly important as scientists inquire to understand behaviors of the global atmosphere at extreme scales. Nowadays, heterogeneous architecture based on both processors and accelerators is becoming an important solution for large-scale computing. However, large-scale simulation of the global atmosphere brings a severe challenge to the development of highly scalable algorithms that fit well into state-of-the-art heterogeneous systems. Although successes have been made on GPU-accelerated computing in some top-level applications, studies on fully exploiting heterogeneous architectures in global atmospheric modeling are still very less to be seen, due in large part to both the computational difficulties of the mathematical models and the requirement of high accuracy for long term simulations. In this paper, we propose a peta-scalable hybrid algorithm that is successfully applied in a cubed-sphere shallow-water model for global atmospheric simulations. We employ an adjustable partition between CPUs and GPUs to achieve a balanced utilization of the entire hybrid system, and present a pipe-flow scheme to conduct conflict-free inter-node communication on the cubed-sphere geometry and to maximize communication-computation overlap. Systematic optimizations for multithreading on both GPU and CPU sides are performed to enhance computing throughput and improve memory efficiency. Our experiments demonstrate nearly ideal strong and weak scalabilities on up to 3,750 nodes of the Tianhe-1A. The largest run sustains a performance of 0.8 Pflops in double precision (32% of the peak performance), using 45,000 CPU cores and 3,750 GPUs.
收录类别	SCI ; EI
语种	英语
内容类型	期刊论文
源URL	[http://ir.nssc.ac.cn/handle/122/4973]
专题	国家空间科学中心_空间科学部
推荐引用方式 GB/T 7714	Yang, Chao,Xue, Wei,Fu, Haohuan,et al. A Peta-scalable CPU-GPU Algorithm for Global Atmospheric Simulations[J]. ACM SIGPLAN NOTICES,2013,48(8):1-11.
APA	Yang, Chao.,Xue, Wei.,Fu, Haohuan.,Gan, Lin.,Li, Linfeng.,...&Zheng, Weimin.(2013).A Peta-scalable CPU-GPU Algorithm for Global Atmospheric Simulations.ACM SIGPLAN NOTICES,48(8),1-11.
MLA	Yang, Chao,et al."A Peta-scalable CPU-GPU Algorithm for Global Atmospheric Simulations".ACM SIGPLAN NOTICES 48.8(2013):1-11.