Parallel ADI Preconditioners for All-Scale Atmospheric Models

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• 关键词：Deflation preconditioners ; ADI ; EULAG
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9574
• 期：1
• 页码：607-618
• 全文大小：385 KB
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• 作者单位：Zbigniew P. Piotrowski (19)
  Bartlomiej Matejczyk (20)
  Leszek Marcinkowski (21)
  Piotr K. Smolarkiewicz (22)
  
  19. Institute of Meteorology and Water Management - National Research Institute, Podlesna 61, 01-673, Warsaw, Poland
  20. Johann Radon Institute for Computational and Applied Mathematics, Linz, Austria
  21. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
  22. European Centre for Medium-Range Weather Forecasts, Reading, UK
  
• 丛书名：Parallel Processing and Applied Mathematics
• ISBN：978-3-319-32152-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Effective preconditioning lies at the heart of multiscale flow simulation, including a broad range of geoscientific applications that rely on semi-implicit integrations of the governing PDEs. For such problems, conditioning of the resulting sparse linear operator directly responds to the squared ratio of largest and smallest spatial scales represented in the model. For thin-spherical-shell geometry of the Earth atmosphere the condition number is enormous, upon which implicit preconditioning is imperative to eliminate the stiffness resulting from relatively fine vertical resolution. Furthermore, the anisotropy due to the meridians convergence in standard latitude-longitude discretizations becomes equally detrimental as the horizontal resolution increases to capture nonhydrostatic dynamics. Herein, we discuss a class of effective preconditioners based on the parallel ADI approach. The approach has been implemented in the established high-performance all-scale model EULAG with flexible computational domain distribution, including a 3D processor array. The efficacy of the approach is demonstrated in the context of an archetypal simulation of global weather.