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The PT-Scotch project: purpose, algorithms, first results

Authors: Chevalier, Cédric; Pellegrini, François;

The PT-Scotch project: purpose, algorithms, first results

Abstract

Graph partitioning is an ubiquitous technique which has applications in many fields of computer science and engineering. It is mostly used to help solving domain dependent optimization problems modeled in terms of weighted or unweighted graphs, where finding good solutions amounts to computing, eventually recursively in a divide-and-conquer framework, small vertex or edge cuts that balance evenly the weights of the graph parts. Because there always exists large problem graphs which cannot fit in the memory of sequential computers and cost too much to partition, parallel graph partitioning tools have been developed. PT-Scotch is another attempt to provide a simple and efficient library for parallel graph partitioning and ordering. We present in this paper the main research topics that we want to cover in this project in order to achieve our goals, as well as some early results.

Country
France
Keywords

[INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], parallel graph partitioning

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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