A survey of high level frameworks in block-structured adaptive mesh refinement packages

Over the last decade block-structured adaptive mesh refinement (SAMR) has found increasing use in large, publicly available codes and frameworks. SAMR frameworks have evolved along different paths. Some have stayed focused on specific domain areas, others have pursued a more general functionality, p...

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Published inJournal of parallel and distributed computing Vol. 74; no. 12; pp. 3217 - 3227
Main Authors Dubey, Anshu, Almgren, Ann, Bell, John, Berzins, Martin, Brandt, Steve, Bryan, Greg, Colella, Phillip, Graves, Daniel, Lijewski, Michael, Löffler, Frank, O’Shea, Brian, Schnetter, Erik, Van Straalen, Brian, Weide, Klaus
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.12.2014
Elsevier
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ISSN0743-7315
1096-0848
DOI10.1016/j.jpdc.2014.07.001

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Summary:Over the last decade block-structured adaptive mesh refinement (SAMR) has found increasing use in large, publicly available codes and frameworks. SAMR frameworks have evolved along different paths. Some have stayed focused on specific domain areas, others have pursued a more general functionality, providing the building blocks for a larger variety of applications. In this survey paper we examine a representative set of SAMR packages and SAMR-based codes that have been in existence for half a decade or more, have a reasonably sized and active user base outside of their home institutions, and are publicly available. The set consists of a mix of SAMR packages and application codes that cover a broad range of scientific domains. We look at their high-level frameworks, their design trade-offs and their approach to dealing with the advent of radical changes in hardware architecture. The codes included in this survey are BoxLib, Cactus, Chombo, Enzo, FLASH, and Uintah. •A survey of mature openly available state-of-the-art structured AMR libraries and codes.•Discussion of their frameworks, challenges and design trade-offs.•Directions being pursued by the codes to prepare for the future many-core and heterogeneous platforms.
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USDOE
AC02-05CH11231; AC05-00OR22725
ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2014.07.001