On the Monotonic Lagrangian Grid as Antecedent to the Neighborhood Grid

We note that a recently described data structure, the Neighborhood Grid, is equivalent to a data structure developed in the mid-1980s called the Monotonic Lagrangian Grid (MLG). The MLG was originally developed to support high-performance molecular and fluid dynamics simulations on both supercompute...

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Vydané v:Journal of parallel and distributed computing Ročník 142; s. 13 - 15
Hlavný autor: Uhlmann, Jeffrey
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Inc 01.08.2020
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ISSN:0743-7315, 1096-0848
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Shrnutí:We note that a recently described data structure, the Neighborhood Grid, is equivalent to a data structure developed in the mid-1980s called the Monotonic Lagrangian Grid (MLG). The MLG was originally developed to support high-performance molecular and fluid dynamics simulations on both supercomputer and vector processing architectures and still finds use in those and other areas. In this paper we emphasize that the rediscovery of the MLG offers benefits to users of the Neighborhood Grid in the form of an existing literature with results relevant to its efficient implementation in various contexts while users of the MLG similarly benefit from new theoretical results obtained for the Neighborhood grid. •The paper notes that the recently introduced Neighborhood Grid is a rediscovery of a known data structure called the Monotonic Lagrangian Grid (MLG).•Background on the MLG and its literature are discussed, and a previously-unpublished result relating to its theoretical properties is provided.•It is argued that the Neighborhood Grid has motivated new theoretical analyses that has proven new results not previously known about the MLG.
ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2020.04.001