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HAMR: The Hierarchical Adaptive Mesh Refinement System

  • Henry Neeman
Conference paper
  • 320 Downloads
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 117)

Abstract

The Hierarchical Adaptive Mesh Refinement (HAMR) system is an autonomous, general purpose, flexible, extensible environment that allows the rapid and convenient conversion of unigrid solvers into structured adaptive mesh refinement (SAMR) implementations. HAMR’s design is based on a theoretical foundation that describes data, methods, their management, and the relationships between them. These elements allow the development not just of SAMR algorithms, but of SAMR algorithms that require absolutely no knowledge about the application to which they are applied.

The theoretical foundation consists of several parts: a complicated data structure representing the strata of a grid hierarchy; scope and extent characteristics; a variety of data types; several kinds of metadata attributes associated with data items, and rules governing them; a specification lookup table that makes the grid hierarchy self-describing and therefore autonomous; and a user-provided declaration, divided into modules, that describes the data and methods associated with an application, and the relationships between them. Data management of these pieces is actually rather uncomplicated. Some implementation issues are also discussed. A contemporary physics experiment is run using HAMR, and HAMR’s performance is examined.

Key words

Structured adaptive mesh refinement problem solving environment 

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Henry Neeman
    • 1
  1. 1.Laboratory for Computational Astrophysics, National Center for Supercomputing ApplicationsUniversity of IllinoisUrbanaUSA

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