Performance and scaling of locally-structured grid methods forpartial differential equations

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In this paper, we discuss some of the issues in obtaining high performance for block-structured adaptive mesh refinement software for partial differential equations. We show examples in which AMR scales to thousands of processors. We also discuss a number of metrics for performance and scalability that can provide a basis for understanding the advantages and disadvantages of this approach.

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Colella, Phillip; Bell, John; Keen, Noel; Ligocki, Terry; Lijewski, Michael & Van Straalen, Brian July 19, 2007.

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In this paper, we discuss some of the issues in obtaining high performance for block-structured adaptive mesh refinement software for partial differential equations. We show examples in which AMR scales to thousands of processors. We also discuss a number of metrics for performance and scalability that can provide a basis for understanding the advantages and disadvantages of this approach.

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  • SciDAC 2007 Conference, Boston, MA,6/25/2007-6/28/2007

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  • Report No.: LBNL--63231
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 927343
  • Archival Resource Key: ark:/67531/metadc893575

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  • July 19, 2007

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  • Sept. 27, 2016, 1:39 a.m.

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  • Sept. 22, 2017, 3:03 p.m.

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Colella, Phillip; Bell, John; Keen, Noel; Ligocki, Terry; Lijewski, Michael & Van Straalen, Brian. Performance and scaling of locally-structured grid methods forpartial differential equations, article, July 19, 2007; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc893575/: accessed May 26, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.