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Search-Space Partitioning for Parallelizing SMT Solvers

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Theory and Applications of Satisfiability Testing -- SAT 2015 (SAT 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,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.

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Authors and Affiliations

  1. Faculty of Informatics, University of Lugano, Via Giuseppe Buffi 13, 6904, Lugano, Switzerland

    Antti E. J. Hyvärinen, Matteo Marescotti & Natasha Sharygina

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  1. Antti E. J. Hyvärinen
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  2. Matteo Marescotti
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  3. Natasha Sharygina
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Correspondence to Antti E. J. Hyvärinen .

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Editors and Affiliations

  1. Algorithms, University of Texas, Austin, Texas, USA

    Marijn Heule

  2. Trusted Systems Research Group, Fort Meade, Texas, USA

    Sean Weaver

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Hyvärinen, A.E.J., Marescotti, M., Sharygina, N. (2015). Search-Space Partitioning for Parallelizing SMT Solvers. In: Heule, M., Weaver, S. (eds) Theory and Applications of Satisfiability Testing -- SAT 2015. SAT 2015. Lecture Notes in Computer Science(), vol 9340. Springer, Cham. https://doi.org/10.1007/978-3-319-24318-4_27

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  • DOI: https://doi.org/10.1007/978-3-319-24318-4_27

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