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An efficient parallel algorithm for the coupling of global climate models and regional climate models on a large-scale multi-core cluster

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Abstract

High-performance computing for climate models has always been an interesting research area. It is valuable to nest a regional climate model within a global climate model, but large-scale simulation of the nesting or coupling severely challenges to the development of efficient parallel algorithms that fit well into multi-core clusters. This paper first presents research on the coupling of the Institute of Atmospheric Physics of Chinese Academy of Sciences Atmospheric General Circulation Model version 4.0 and the Weather Research and Forecasting model, then proposes an efficient parallel algorithm of the coupling. The algorithm includes initialization of input data, decomposition of computing grid and processes, parallel computing of component models, and data exchange by a coupler. By calling some subroutines of the Model Coupling Toolkit, the parallelization of the proposed algorithm is implemented. Experiments show that the parallel algorithm is very effective and scalable. The parallel efficiency of the algorithm on 1,024 CPU cores can reach up to 70%. Moreover, its parallel efficiency with respect to weak scalability is 72.56% on a multi-core cluster.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61602477), National Key Research and Development Program of China (No. 2016YFB0200800), China Postdoctoral Science Foundation (No. 2016M601158), the Fundamental Research Funds for the Central Universities (No. 2652017113), Open Research Project of the Hubei Key Laboratory of Intelligent Geo-Information Processing (No. KLIGIP-2017A04), Knowledge Innovation Program of the Chinese Academy of Sciences (No. XXH13504-03-02), and Open Project Program of the State Key Laboratory of Mathematical Engineering and Advanced Computing.

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Authors and Affiliations

  1. School of Information Engineering, China University of Geosciences, Beijing, 100083, China

    Yuzhu Wang

  2. Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, 430074, China

    Yuzhu Wang

  3. Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100190, China

    Jinrong Jiang & Xuebin Chi

  4. State Key Laboratory of Mathematical Engineering and Advanced Computing, Wuxi, 214125, China

    Jinrong Jiang

  5. School of Computer Science, China University of Geosciences, Wuhan, 430074, China

    Junqiang Zhang

  6. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Juanxiong He & He Zhang

  7. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Tianxiang Yue

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  1. Yuzhu Wang
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  2. Jinrong Jiang
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  3. Junqiang Zhang
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  4. Juanxiong He
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  5. He Zhang
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Correspondence to Yuzhu Wang or Jinrong Jiang.

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Wang, Y., Jiang, J., Zhang, J. et al. An efficient parallel algorithm for the coupling of global climate models and regional climate models on a large-scale multi-core cluster. J Supercomput 74, 3999–4018 (2018). https://doi.org/10.1007/s11227-018-2406-6

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