Access Restriction

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

Open content in new tab

   Open content in new tab
Source: ACM Digital Library