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Search-Space Partitioning for Parallelizing SMT Solvers

  • Antti E. J. Hyvärinen
  • Matteo Marescotti
  • Natasha Sharygina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9340)

Abstract

This paper studies how parallel computing can be used to reduce the time required to solve instances of the Satisfiability Modulo Theories problem (SMT). We address the problem in two orthogonal ways: (i) by distributing the computation using algorithm portfolios, search space partitioning techniques, and their combinations; and (ii) by studying the effect of partitioning heuristics, and in particular the lookahead heuristic, to the efficiency of the partitioning. We implemented the approaches in the OpenSMT2 solver and experimented with the QF_UF theory on a computing cloud. The results show a consistent speed-up on hard instances with up to an order of magnitude run time reduction and more instances being solved within the timeout compared to the sequential implementation.

Keywords

Conjunctive Normal Form Truth Assignment Hard Instance Conjunctive Normal Form Formula Portfolio Approach 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Antti E. J. Hyvärinen
    • 1
  • Matteo Marescotti
    • 1
  • Natasha Sharygina
    • 1
  1. 1.Faculty of InformaticsUniversity of LuganoLuganoSwitzerland

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