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A scalable parallel algorithm for atmospheric general circulation models on a multi-core cluster

Lookup NU author(s): Professor Raj Ranjan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

© 2017 Elsevier B.V. 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.


Publication metadata

Author(s): Wang Y, Jiang J, Zhang H, Dong X, Wang L, Ranjan R, Zomaya AY

Publication type: Article

Publication status: Published

Journal: Future Generation Computer Systems

Year: 2017

Volume: 72

Pages: 1-10

Print publication date: 01/07/2017

Online publication date: 09/02/2017

Acceptance date: 06/02/2017

Date deposited: 20/08/2017

ISSN (print): 0167-739X

ISSN (electronic): 1872-7115

Publisher: Elsevier B.V.

URL: https://doi.org/10.1016/j.future.2017.02.008

DOI: 10.1016/j.future.2017.02.008


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