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• W2281633864 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." @default.
• W2281633864 created "2016-06-24" @default.
• W2281633864 creator A5062525448 @default.
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• W2281633864 date "2015-01-01" @default.
• W2281633864 modified "2023-10-18" @default.
• W2281633864 title "Search-Space Partitioning for Parallelizing SMT Solvers" @default.
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• W2281633864 doi "https://doi.org/10.1007/978-3-319-24318-4_27" @default.
• W2281633864 hasPublicationYear "2015" @default.
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