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Scientific Programming
Volume 8, Issue 1, Pages 49-57

Design and Performance Analysis of a Massively Parallel Atmospheric General Circulation Model

Daniel S. Schaffer and Max J. Suárez

NASA Seasonal to Interannual Prediction Project, NASA Goddard Space Flight Center, Code 971, Greenbelt, MD 20771, USA

Received 11 October 2000; Accepted 11 October 2000

Copyright © 2000 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Christian L. Keppenne, and Michele M. Rienecker, “Initial Testing of a Massively Parallel Ensemble Kalman Filter with the Poseidon Isopycnal Ocean General Circulation Model,” Monthly Weather Review, vol. 130, no. 12, pp. 2951–2965, 2002. View at Publisher · View at Google Scholar
  • Christian L. Keppenne, and Michele M. Rienecker, “Assimilation of temperature into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter,” Journal of Marine Systems, vol. 40-41, pp. 363–380, 2003. View at Publisher · View at Google Scholar
  • Aimé Fournier, Mark A. Taylor, and Joseph J. Tribbia, “The Spectral Element Atmosphere Model (SEAM): High-resolution parallel computation and localized resolution of regional dynamics,” Monthly Weather Review, vol. 132, no. 3, pp. 726–748, 2004. View at Publisher · View at Google Scholar
  • Chris Hill, Robert Hallberg, Anthony Craig, David Neckels, Jay Larson, Arlindo Da Silva, William Sawyer, Carlos Cruz, Leonid Zaslavsky, Byron Boville, Nancy Collins, Erik Kluzek, John Michalakes, Earl Schwab, Shepard Smithline, Jon Wolfe, Cecelia DeLuca, Mark Iredell, Weiyu Yang, Robert Jacob, Balaji, Max Suarez, and Atanas Trayanov, “Implementing applications with the earth system modeling framework,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3732, pp. 563–572, 2006. View at Publisher · View at Google Scholar
  • Li Liu, Ruizhe Li, Guangwen Yang, Bin Wang, Lijuan Li, and Ye Pu, “Improving Parallel Performance of a Finite-Difference AGCM on Modern High-Performance Computers,” Journal Of Atmospheric And Oceanic Technology, vol. 31, no. 10, pp. 2157–2168, 2014. View at Publisher · View at Google Scholar