Informatics and Applications
2017, Volume 11, Issue 3, pp 113122
ON PARALLELIZATION OF ASYMPTOTICALLY OPTIMAL DUALIZATION ALGORITHMS
 E. V. Djukova
 A. G. Nikiforov
 P. A. Prokofyev
Abstract
The main goal of the paper is to develop and implement an approach to building efficient parallel algorithms for intractable enumeration problems and to apply this approach to one of the central enumeration problems, i. e., dualization. Asymptotically optimal algorithms for dualization are considered to be the fastest among the known ones. They have a theoretical justification of the efficiency on average. The size of enumerated set in the dualization problem grows exponentially with the size of the input; thus, parallel computations are reasonable to be utilized. The authors introduce the static parallelizing scheme for asymptotically optimal algorithms of dualization and present the results of the testing. Statistical processing of the experimental results is conducted in order to determine the kind of distribution of the random variables, representing the size of the subtasks for parallel computation. The conditions, under which the schema demonstrates almost maximum speedup and quite uniform processors load, are discovered.
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[+] About this article
Title
ON PARALLELIZATION OF ASYMPTOTICALLY OPTIMAL DUALIZATION ALGORITHMS
Journal
Informatics and Applications
2017, Volume 11, Issue 3, pp 113122
Cover Date
20170930
DOI
10.14357/19922264170313
Print ISSN
19922264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
discrete enumeration problem; dualization; asymptotically optimal algorithm; irreducible covering of a Boolean matrix; polynomialtime delay algorithm; parallel dualization algorithm
Authors
E. V. Djukova , , A. G. Nikiforov , and P. A. Prokofyev
Author Affiliations
Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 442 Vavilov Str., Moscow 119333, Russian Federation
M.V. Lomonosov Moscow State University, M.V. Lomonosov Moscow State University, 152 Leninskiye Gory, GSP1, Moscow 119991, Russian Federation
Technische University of Munich, 21 Arcisstrasse, Munich 80333, Germany
