Embarrassingly Parallel Search

  • Jean-Charles Régin
  • Mohamed Rezgui
  • Arnaud Malapert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8124)

Abstract

We propose the Embarrassingly Parallel Search, a simple and efficient method for solving constraint programming problems in parallel. We split the initial problem into a huge number of independent subproblems and solve them with available workers, for instance cores of machines. The decomposition into subproblems is computed by selecting a subset of variables and by enumerating the combinations of values of these variables that are not detected inconsistent by the propagation mechanism of a CP Solver. The experiments on satisfaction problems and optimization problems suggest that generating between thirty and one hundred subproblems per worker leads to a good scalability. We show that our method is quite competitive with the work stealing approach and able to solve some classical problems at the maximum capacity of the multi-core machines. Thanks to it, a user can parallelize the resolution of its problem without modifying the solver or writing any parallel source code and can easily replay the resolution of a problem.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jean-Charles Régin
    • 1
  • Mohamed Rezgui
    • 1
  • Arnaud Malapert
    • 1
  1. 1.I3S UMR 6070, CNRSUniversité Nice-Sophia AntipolisFrance

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