SFC-based Communication Metadata Encoding for Adaptive Mesh
Schreiber, M; Weinzierl, T; Bungartz, H-J
Date: 1 October 2013
Conference paper
Publisher
IOS Press
Publisher DOI
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Abstract
The present paper studies two adaptive mesh refinement (AMR) codes
whose grids rely on recursive subdivison in combination with space-filling curves
(SFCs). A non-overlapping domain decomposition based upon these SFCs yields
several well-known advantageous properties with respect to communication demands,
balancing, and partition ...
The present paper studies two adaptive mesh refinement (AMR) codes
whose grids rely on recursive subdivison in combination with space-filling curves
(SFCs). A non-overlapping domain decomposition based upon these SFCs yields
several well-known advantageous properties with respect to communication demands,
balancing, and partition connectivity. However, the administration of the
meta data, i.e. to track which partitions exchange data in which cardinality, is nontrivial
due to the SFC’s fractal meandering and the dynamic adaptivity. We introduce
an analysed tree grammar for the meta data that restricts it without loss of
information hierarchically along the subdivision tree and applies run length encoding.
Hence, its meta data memory footprint is very small, and it can be computed
and maintained on-the-fly even for permanently changing grids. It facilitates a forkjoin
pattern for shared data parallelism. And it facilitates replicated data parallelism
tackling latency and bandwidth constraints respectively due to communication in
the background and reduces memory requirements by avoiding adjacency information
stored per element. We demonstrate this at hands of shared and distributed
parallelized domain decompositions.
Computer Science
Faculty of Environment, Science and Economy
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