Parallel Solving of Quantified Boolean Formulas

Lonsing, Florian; Seidl, Martina

doi:10.1007/978-3-319-63516-3_4

Cited by 2 publications

(3 citation statements)

References 65 publications

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“…In practical QBF solving, attempts to parallelize and distribute QBF solvers have a long history (cf. [18] for a survey). Already more than 20 years back, the first distributed QBF solver PQSolve [4] was presented, in a time when QCDCL had not been invented yet.…”

Section: Related Workmentioning

confidence: 99%

“…In ParaQooba, we now also parallelize each solver call over several QBF solvers with orthogonal strategies. Compared to prior approaches [18], we run a portfolio of multiple solvers in the leaves of the solve tree instead of only parallelizing its root. Having just one tree leads to several advantages: We are more flexible and may also call a preprocessor (e.g.…”

Section: Paracoobamentioning

confidence: 99%

“…Despite the vivid development in sequential QBF solving, only few approaches have been presented for parallel and distributed QBF solving [18]. The most recent parallel QBF solvers are HordeQBF [1] which integrates sequential QCDCL-based solvers to obtain a parallel QBF solver and, more recently, a basic implementation of a QBF module based on the parallel SAT solver Para-Cooba [6] with DepQBF as its only backend solver.…”

Section: Introductionmentioning

confidence: 99%

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ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving

Heisinger¹,

Seidl²,

Biere³

2023

Lecture Notes in Computer Science

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Over the last years, innovative parallel and distributed SAT solving techniques were presented that could impressively exploit the power of modern hardware and cloud systems. Two approaches were particularly successful: (1) search-space splitting in a Divide-and-Conquer (D &C) manner and (2) portfolio-based solving. The latter executes different solvers or configurations of solvers in parallel. For quantified Boolean formulas (QBFs), the extension of propositional logic with quantifiers, there is surprisingly little recent work in this direction compared to SAT.In this paper, we present ParaQooba, a novel framework for parallel and distributed QBF solving which combines D &C parallelization and distribution with portfolio-based solving. Our framework is designed in such a way that it can be easily extended and arbitrary sequential QBF solvers can be integrated out of the box, without any programming effort. We show how ParaQooba orchestrates the collaboration of different solvers for joint problem solving by performing an extensive evaluation on benchmarks from QBFEval’22, the most recent QBF competition.

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Section: Related Workmentioning

confidence: 99%

Section: Paracoobamentioning

confidence: 99%