Proceedings ArticleDOI
Chaff: engineering an efficient SAT solver
Matthew W. Moskewicz,Conor F. Madigan,Ying Zhao,Lintao Zhang,Sharad Malik +4 more
- pp 530-535
TLDR
The development of a new complete solver, Chaff, is described which achieves significant performance gains through careful engineering of all aspects of the search-especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy.Abstract:
Boolean satisfiability is probably the most studied of the combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in electronic design automation (EDA), as well as in artificial intelligence (AI). This study has culminated in the development of several SAT packages, both proprietary and in the public domain (e.g. GRASP, SATO) which find significant use in both research and industry. Most existing complete solvers are variants of the Davis-Putnam (DP) search algorithm. In this paper we describe the development of a new complete solver, Chaff which achieves significant performance gains through careful engineering of all aspects of the search-especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy. Chaff has been able to obtain one to two orders of magnitude performance improvement on difficult SAT benchmarks in comparison with other solvers (DP or otherwise), including GRASP and SATO.read more
Citations
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Journal ArticleDOI
Search for Steady States of Piecewise-Linear Differential Equation Models of Genetic Regulatory Networks
H. de Jong,Michel Page +1 more
TL;DR: The problem of finding all steady states of genetic regulatory networks described by piecewise-linear differential equation (PLDE) models is shown to be NP-hard and translated into the problem ofFinding all valuations of a propositional satisfiability (SAT) formula.
Posted Content
Guiding High-Performance SAT Solvers with Unsat-Core Predictions
Daniel Selsam,Nikolaj Bjørner +1 more
TL;DR: In this article, the authors train a simplified NeuroSAT architecture to directly predict the unsatisfiable cores of real problems, and modify several high-performance SAT solvers to periodically replace their variable activity scores with neuroSAT's prediction of how likely variables are to appear in an unsatisfiable core.
Proceedings ArticleDOI
TORSCHE Scheduling toolbox for Matlab
TL;DR: The toolbox is intended mainly as a research tool to handle control and scheduling co-design problems and provides an interface to a real-time Matlab/Simulik based simulator TrueTime and a code generator allowing to generate parallel code for FPGA.
Journal ArticleDOI
Computing finite models by reduction to function-free clause logic
TL;DR: In this article, a model search procedure for finite models of first-order logic specifications is presented, based on reducing model search to a sequence of propositional satisfiability problems and applying (ecient) reasoning.
Book ChapterDOI
Analyzing Context-Free Grammars Using an Incremental SAT Solver
TL;DR: B bounded versions of undecidable problems about context-free languages which restrict the domain of words to some finite length are considered and fully utilizing the power of incrementat SAT solvers prove correctness and validate this approach with benchmarks.
References
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Book
Computers and Intractability: A Guide to the Theory of NP-Completeness
TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI
Tabu Search—Part II
TL;DR: The elements of staged search and structured move sets are characterized, which bear on the issue of finiteness, and new dynamic strategies for managing tabu lists are introduced, allowing fuller exploitation of underlying evaluation functions.
Book ChapterDOI
Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey
TL;DR: In this article, the authors survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory, and indicate some problems for future research and include a selective bibliography.
Book
A machine program for theorem-proving
TL;DR: The programming of a proof procedure is discussed in connection with trial runs and possible improvements.