Parallel SAT Solver Selection and Scheduling

  • Yuri Malitsky
  • Ashish Sabharwal
  • Horst Samulowitz
  • Meinolf Sellmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7514)


Combining differing solution approaches by means of solver portfolios has proven as a highly effective technique for boosting solver performance. We consider the problem of generating parallel SAT solver portfolios. Our approach is based on a recently introduced sequential SAT solver portfolio that excelled at the last SAT competition. We show how the approach can be generalized for the parallel case, and how obstacles like parallel SAT solvers and symmetries induced by identical processors can be overcome. We compare different ways of computing parallel solver portfolios with the best performing parallel SAT approaches to date. Extensive experimental results show that the developed methodology very significantly improves our current parallel SAT solving capabilities.


Column Generation Training Instance Static Schedule Execution Phase Integer Program Formulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuri Malitsky
    • 1
  • Ashish Sabharwal
    • 2
  • Horst Samulowitz
    • 2
  • Meinolf Sellmann
    • 2
  1. 1.Cork Constraint Computation CentreUniversity College CorkIreland
  2. 2.IBM Watson Research CenterYorktown HeightsUSA

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