Observations from Parallelising Three Maximum Common (Connected) Subgraph Algorithms

Hoffmann, R., Mccreesh, C. , Ndiaye, S. N., Prosser, P. , Reilly, C., Solnon, C. and Trimble, J. (2018) Observations from Parallelising Three Maximum Common (Connected) Subgraph Algorithms. In: 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2018), Delft, The Netherlands, 26-29 Jun 2018, pp. 298-315. ISBN 9783319930305 (doi: 10.1007/978-3-319-93031-2_22)

157151.pdf - Accepted Version



We discuss our experiences adapting three recent algorithms for maximum common (connected) subgraph problems to exploit multi-core parallelism. These algorithms do not easily lend themselves to parallel search, as the search trees are extremely irregular, making balanced work distribution hard, and runtimes are very sensitive to value-ordering heuristic behaviour. Nonetheless, our results show that each algorithm can be parallelised successfully, with the threaded algorithms we create being clearly better than the sequential ones. We then look in more detail at the results, and discuss how speedups should be measured for this kind of algorithm. Because of the difficulty in quantifying an average speedup when so-called anomalous speedups (superlinear and sublinear) are common, we propose a new measure called aggregate speedup.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Trimble, Mr James and REILLY, Craig and Mccreesh, Dr Ciaran and Prosser, Dr Patrick and Hoffmann, Dr Ruth
Authors: Hoffmann, R., Mccreesh, C., Ndiaye, S. N., Prosser, P., Reilly, C., Solnon, C., and Trimble, J.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2018 Springer International Publishing AG, part of Springer Nature
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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