HordeQBF: A Modular and Massively Parallel QBF Solver

Balyo, Tomáš; Lonsing, Florian

doi:10.1007/978-3-319-40970-2_33

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…As indicated by its name, it is tailored around the sequential QBF solver DepQBF [17]. Another recent MPI-based QBF solver is HordeQBF [1] which implements knowledge sharing for QCDCL solvers. It is designed in such a way that it allows the integration of any QCDCL solver.…”

Section: Related Workmentioning

confidence: 99%

“…6: Preprocessed formulas of the Hex positional game planning [20,25] benchmarks from the QBF22 benchmark set. Also compared to HordeQBF [1] as available state-of-the-art parallel QBF solver.…”

Section: Overall Performance Comparisonmentioning

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. To the best of our knowledge, besides these two approaches no other parallel QBF solver has recently been presented.…”

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: Overall Performance Comparisonmentioning

confidence: 99%

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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“…In the field of quantified boolean formulas (QBF), Balyo et al used a portfolio approach [28], similar to the one they used in [29] and report super-linear speedups. Unfortunately, most of this improvement can be achieved with 2 nodes, each of which uses 4 processes with 4 solver threads, which is 32 threads altogether.…”

Section: Parallel Constraint Programmingmentioning

confidence: 99%

SAT and CP - Parallelisation and Applications

Ehlers¹

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In this thesis, we consider the parallelisation and application of SAT and CP solvers. In the first chapter, we consider SAT, the decision problem of propositional logic. We discuss details of the implementations of SAT solvers, and show how to improve upon existing sequential solvers. Furthermore, we discuss the parallelisation of these solvers with a focus on the communication of intermediate results within a parallel solver. The second chapter is concerned with Contraint Programing (CP) with learning. Contrary to classical Constraint Programming techniques, this incorporates learning mechanisms as they are used in the field of SAT solving. We present results from parallelising CHUFFED, a learning CP solver. In the final chapter, we discuss Sorting Networks, which are data oblivious sorting algorithms. Their independence of the input data lends them to parallel implementation. We consider the question how many parallel sorting steps are needed to sort some inputs, and present both lower and upper bounds for several cases.

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Parallel Solving of Quantified Boolean Formulas

Lonsing

Seidl

2018

Handbook of Parallel Constraint Reasoning

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HordeQBF: A Modular and Massively Parallel QBF Solver

Cited by 6 publications

References 23 publications

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

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

SAT and CP - Parallelisation and Applications

Parallel Solving of Quantified Boolean Formulas

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