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URN: urn:nbn:de:0030-drops-20818
URL: https://drops.dagstuhl.de/opus/volltexte/2009/2081/
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Bisseling, Rob ; van Leeuwen, Tristan ; Catalyurek, Umit V.

Combinatorial Problems in High-Performance Computing: Partitioning

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09061.BisselingRob.ExtAbstract.2081.pdf (0.09 MB)


Abstract

This extended abstract presents a survey of combinatorial problems
encountered in scientific computations on today's
high-performance architectures, with sophisticated memory
hierarchies, multiple levels of cache, and multiple processors
on chip as well as off-chip.
For parallelism, the most important problem is to partition
sparse matrices, graph, or hypergraphs into nearly equal-sized
parts while trying to reduce inter-processor communication.
Common approaches to such problems involve multilevel
methods based on coarsening and uncoarsening (hyper)graphs,
matching of similar vertices, searching for good separator sets
and good splittings, dynamical adjustment of load imbalance,
and two-dimensional matrix splitting methods.

BibTeX - Entry

@InProceedings{bisseling_et_al:DSP:2009:2081,
  author =	{Rob Bisseling and Tristan van Leeuwen and Umit V. Catalyurek},
  title =	{Combinatorial Problems in High-Performance Computing: Partitioning},
  booktitle =	{Combinatorial Scientific Computing},
  year =	{2009},
  editor =	{Uwe Naumann and Olaf Schenk and Horst D. Simon and Sivan Toledo},
  number =	{09061},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2009/2081},
  annote =	{Keywords: Partitioning, sparse matrix, hypergraph, parallel, HPC}
}

Keywords: Partitioning, sparse matrix, hypergraph, parallel, HPC
Collection: 09061 - Combinatorial Scientific Computing
Issue Date: 2009
Date of publication: 24.07.2009


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