Authors:
Wang Yuzhu1,2 Jiang Jinrong2 Zhang He3 Dong Xiao3 Wang Lizhe4,1 Ranjan Rajiv5 and Zomaya Y. Albert6
1 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, China
2 Computer Network Information Center, Chinese Academy of Sciences, China
3 International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
4 School of Computer Science, China University of Geosciences, China
5 School of Computing Science, Newcastle University, United Kingdom
6 School of Information Technologies, The University of Sydney, Australia
Abstract:
High-performance computing of atmospheric general circulation models (AGCMs) has been receiving increasing attention in earth science research. However, when scaling to large-scale multi-core computing, the parallelization of an AGCM which demands fast parallel computing for long-time integration or climate simulation becomes extremely challenging due to its inner complex numerical calculation. The previous Institute of Atmospheric Physics of the Chinese Academy of Sciences Atmospheric General Circulation Model version 4.0 (IAP AGCM4.0) with one-dimensional domain decomposition can only run on dozens of CPU cores, so the paper proposes a two-dimensional domain decomposition parallel algorithm for it. In the parallel implementation of the IAP AGCM4.0, its dynamical core utilizes a hybrid form of latitude/longitude decomposition and vertical direction/longitude circle direction decomposition. Through experiments on a multi-core cluster, we confirmed that our algorithm is efficient and scalable. The parallel efficiency of the IAP AGCM4.0 can reach up to 50.88% on 512 CPU cores, and the IAP AGCM4.0 can be run long-term simulations for climate change research.
Key words:
High performance computing, Parallel algorithm, Domain decomposition, Atmospheric general circulation model
Citation:
Y. Wang, J. Jiang, H. Zhang, X. Dong, L. Wang, R. Ranjan, A.Y. Zomaya, 2017: A scalable parallel algorithm for atmospheric general circulation models on a multicore cluster. Future Generation Computer Systems, 72, 1-10,
http://dx.doi.org/10.1016/j.future.2017.02.008.
