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c-sat: A Parallel SAT Solver for Clusters
2009Parallelizing modern SAT solvers for clusters such as Beowulf is an important challenge both in terms of performance scalability and stability. This paper describes a SAT Solver c-sat, a parallelization of MiniSat using MPI. It employs a layered master-worker architecture, where the masters handle lemma exchange, deletion of redundant lemmas and the ...
Kei Ohmura, Kazunori Ueda
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A Preprocessor for Max-SAT Solvers
2008We describe a preprocessor that incorporates a variable saturation procedure for Max-SAT, and provide empirical evidence that it improves the performance of some of the most successful state-of-the-art solvers on several partial (weighted) Max-SAT instances of the 2007 Max-SAT Evaluation.
Josep Argelich +2 more
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SAT-to-SAT: Declarative Extension of SAT Solvers with New Propagators
Proceedings of the AAAI Conference on Artificial Intelligence, 2016Special-purpose propagators speed up solving logic programs by inferring facts that are hard to deduce otherwise. However, implementing special-purpose propagators is a non-trivial task and requires expert knowledge of solvers. This paper proposes a novel approach in logic programming that allows (1) logical specification of both the ...
Tomi Janhunen +2 more
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An Adaptive Parallel SAT Solver
2016We present and evaluate AmPharoS, a new parallel SAT solver based on the divide and conquer paradigm. This solver, designed to work on a great number of cores, runs workers on sub-formulas restricted to cubes. In addition to classical clause sharing, it also exchange extra information associated to the cubes.
Gilles Audemard +3 more
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SAT-Hard: A Learning-Based Hardware SAT-Solver
2019 22nd Euromicro Conference on Digital System Design (DSD), 2019Within the last decades, tremendous research work has been carried out on the development of software-based algorithms to solve the Boolean Satisfiability Problem. These SAT-solvers have then been heavily orchestrated for addressing complex computational tasks like the verification of circuits. In this field, most of the applied techniques focused only
Buse Ustaoglu +4 more
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Planning with Specialized SAT Solvers
Proceedings of the AAAI Conference on Artificial Intelligence, 2011Logic, and declarative representation of knowledge in general, have long been a preferred framework for problem solving in AI. However, specific subareas of AI have been eager to abandon general-purpose knowledge representation in favor of methods that seem to address their computational core problems better.
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Zchaff2004: An Efficient SAT Solver
2005The Boolean Satisfiability Problem (SAT) is a well known NP-Complete problem. While its complexity remains a source of many interesting questions for theoretical computer scientists, the problem has found many practical applications in recent years. The emergence of efficient SAT solvers which can handle large structured SAT instances has enabled the ...
Yogesh S. Mahajan +2 more
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On the parallelization of SAT solvers
2015 Tenth International Conference on Computer Engineering & Systems (ICCES), 2015This paper presents the main challenges, the hot topics, and the intriguing issues in the area of parallel SAT solving which provides possible directions for future research. It gives a detailed summary for the main features and technologies used in the most widely known and successful parallel SAT solvers and shows the strong points and the ...
Yasmeen Abd El Khalek +2 more
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Probabilistic Reasoning by SAT Solvers
2009In a series of papers we have shown that fundamental probabilistic reasoning problems can be encoded as hybrid probabilistic logic programs with probabilistic answer set semantics described in [24]. These probabilistic reasoning problems include, but not limited to, probabilistic planning [28], probabilistic planning with imperfect sensing actions [29],
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2007
As SAT becomes more popular due to its ability to handle large real-world problems, progress in efficiency appears to have slowed down over the past few years. On the other hand, we now have access to many sophisticated implementations of SAT solvers, sometimes boasting large amounts of code. Although low-level optimizations can help, we argue that the
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As SAT becomes more popular due to its ability to handle large real-world problems, progress in efficiency appears to have slowed down over the past few years. On the other hand, we now have access to many sophisticated implementations of SAT solvers, sometimes boasting large amounts of code. Although low-level optimizations can help, we argue that the
openaire +1 more source