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Volume 20 Issue 1

Jan.  2003

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2003 >  20(1): 159-163

Distributed Parallelization of a Global Atmospheric Data Objective Analysis System

  • 1.

    College of Computer Science, National University of Defense Technology, Changsha 410073,College of Computer Science, National University of Defense Technology, Changsha 410073,Meteorological Center of Airforce, Beijing 100843


doi: 10.1007/BF03342060

  • It is difficult to parallelize a subsistent sequential algorithm. Through analyzing the sequentialalgorithm of a Global Atmospheric Data Objective Analysis System, this article puts forward a distributedparallel algorithm that statically distributes data on a massively parallel processing (MPP) computer.The algorithm realizes distributed parallelization by extracting the analysis boxes and model grid pointlatitude rows with leaped steps, and by distributing the data to different processors. The parallel algorithmachieves good load balancing, high parallel efficiency, and low parallel cost. Performance experiments ona MPP computer are also presented.
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    [9] Banglin ZHANG, Vijay TALLAPRAGADA, Fuzhong WENG, Jason SIPPEL, Zaizhong MA, 2015: Use of Incremental Analysis Updates in 4D-Var Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1575-1582.  doi: 10.1007/s00376-015-5041-7
    [10] Zhang Renhe, Zhao Gang, Tan Yanke, 2001: Meridional Wind Stress Anomalies over Tropical Pacific and the Onset of El Nino. Part Ⅰ: Data Analysis, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 467-480.  doi: 10.1007/s00376-001-0038-9
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    • Manuscript History

    Manuscript received: 10 January 2003
    Manuscript revised: 10 January 2003
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Distributed Parallelization of a Global Atmospheric Data Objective Analysis System

    • 1. College of Computer Science, National University of Defense Technology, Changsha 410073,College of Computer Science, National University of Defense Technology, Changsha 410073,Meteorological Center of Airforce, Beijing 100843
    • Manuscript received: 2003-01-10
    • Manuscript revised: 2003-01-10

    Abstract: It is difficult to parallelize a subsistent sequential algorithm. Through analyzing the sequentialalgorithm of a Global Atmospheric Data Objective Analysis System, this article puts forward a distributedparallel algorithm that statically distributes data on a massively parallel processing (MPP) computer.The algorithm realizes distributed parallelization by extracting the analysis boxes and model grid pointlatitude rows with leaped steps, and by distributing the data to different processors. The parallel algorithmachieves good load balancing, high parallel efficiency, and low parallel cost. Performance experiments ona MPP computer are also presented.

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