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Author Auer, B O Fagginger ♦ Bisseling, R. H.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Column intersection graphs ♦ Heuristic algorithms ♦ Weighted graph matching
Abstract To improve the quality and efficiency of hypergraph-based matrix partitioners, we investigate high-quality matchings in column intersection graphs of large sparse binary matrices. We show that such algorithms have a natural decomposition in an integer-weighted graph-matching function and a neighbor-finding function and study the performance of 16 combinations of these functions. We improve upon the original matching algorithm of the Mondriaan matrix partitioner: by using PGA’, we improve the average matching quality from 95.3% to 97.4% of the optimum value; by using our new neighbor-finding heuristic, we obtain comparable quality and speedups of up to a factor of 19.6.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-01-07
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 19
Page Count 22
Starting Page 1.1
Ending Page 1.22


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Source: ACM Digital Library