Abstract
AbstractAs multi-core computing is now standard, it seems irresponsible for constraints researchers to ignore the implications of it. Researchers need to address a number of issues to exploit parallelism, such as: investigating which constraint algorithms are amenable to parallelisation; whether to use shared memory or distributed computation; whether to use static or dynamic decomposition; and how to best exploit portfolios and cooperating search. We review the literature, and see that we can sometimes do quite well, some of the time, on some instances, but we are far from a general solution. Yet there seems to be little overall guidance that can be given on how best to exploit multi-core computers to speed up constraint solving. We hope at least that this survey will provide useful pointers to future researchers wishing to correct this situation.
Publisher
Cambridge University Press (CUP)
Subject
Artificial Intelligence,Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software
Reference165 articles.
1. The distributed breakout algorithms
2. Automatic construction of parallel portfolios via algorithm configuration
3. Aigner M. , Biere A. , Kirsch C. M. , Niemetz A. and Preiner M. 2013. Analysis of portfolio-style parallel SAT solving on current multi-core architectures. In POS@ SAT. 28–40.
4. Automatically improving constraint models in Savile Row
5. Nguyen T. and Deville Y. 1995. A distributed arc-consistency algorithm. In Proc. of 1st International Workshop on Concurrent Constraint Satisfaction.
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