Efficient, scalable hardware engine for Boolean satisfiability and unsatisfiable core extraction

2008 ◽  
Vol 2 (3) ◽  
pp. 214 ◽  
Author(s):  
K. Gulati ◽  
M. Waghmode ◽  
S.P. Khatri ◽  
W. Shi
Keyword(s):  
Boolean Satisfiability ◽  
Scalable Hardware ◽  
Unsatisfiable Core ◽  
Core Extraction

An ant colony algorithm for minimum unsatisfiable core extraction

2008 ◽  
Vol 25 (5) ◽  
pp. 652-660
Author(s):  
Jianmin Zhang ◽  
Shengyu Shen ◽  
Sikun Li
Keyword(s):  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Unsatisfiable Core ◽  
Core Extraction

scholarly journals Abstract Cores in Implicit Hitting Set MaxSat Solving (Extended Abstract)

2021 ◽  
Author(s):  
Jeremias Berg ◽  
Fahiem Bacchus ◽  
Alex Poole
Keyword(s):  
Linear Programming ◽  
Optimization Problems ◽  
State Of The Art ◽  
Empirical Evaluation ◽  
Boolean Satisfiability ◽  
Compact Representation ◽  
Maximum Satisfiability ◽  
Hitting Set ◽  
Combinatorial Optimization Problems ◽  
Core Extraction

Maximum satisfiability (MaxSat) solving is an active area of research motivated by numerous successful applications to solving NP-hard combinatorial optimization problems. One of the most successful approaches for solving MaxSat instances from real world domains are the so called implicit hitting set (IHS) solvers. IHS solvers decouple MaxSat solving into separate core-extraction (i.e. reasoning) and optimization steps which are tackled by a Boolean satisfiability (SAT) and an integer linear programming (IP) solver, respectively. While the approach shows state-of-the-art performance on many industrial instances, it is known that there exists instances on which IHS solvers need to extract an exponential number of cores before terminating. Motivated by the simplest of these problematic instances, we propose abstract cores, a compact representation for a potentially exponential number of regular cores. We demonstrate how to incorporate abstract core reasoning into the IHS algorithm and report on an empirical evaluation demonstrating, that including abstract cores into a state-of-the-art IHS solver improves its performance enough to surpass the best performing solvers of the 2019 MaxSat Evaluation.

A scalable hardware render accelerator using a modified scanline algorithm

1992 ◽  
Vol 26 (2) ◽  
pp. 241-248 ◽  
Author(s):  
Michael Kelley ◽  
Stephanie Winner ◽  
Kirk Gould
Keyword(s):  
Scalable Hardware

Unsatisfiable Core Analysis and Aggregates for Optimum Stable Model Search

2020 ◽  
Vol 176 (3-4) ◽  
pp. 271-297
Author(s):  
Mario Alviano ◽  
Carmine Dodaro
Keyword(s):  
State Of The Art ◽  
Answer Set Programming ◽  
Efficient Algorithms ◽  
Satisfiability Problem ◽  
Core Analysis ◽  
Stable Model ◽  
Maximum Satisfiability ◽  
Model Search ◽  
Unsatisfiable Core ◽  
Stable Models

Many efficient algorithms for the computation of optimum stable models in the context of Answer Set Programming (ASP) are based on unsatisfiable core analysis. Among them, algorithm OLL was the first introduced in the context of ASP, whereas algorithms ONE and PMRES were first introduced for solving the Maximum Satisfiability problem (MaxSAT) and later on adapted to ASP. In this paper, we present the porting to ASP of another state-of-the-art algorithm introduced for MaxSAT, namely K, which generalizes ONE and PMRES. Moreover, we present a new algorithm called OLL-IN-ONE that compactly encodes all aggregates of OLL by taking advantage of shared aggregate sets propagators. The performance of the algorithms have been empirically compared on instances taken from the latest ASP Competition.

Efficient and Scalable Hardware-Based Multicast in Fat-Tree Networks

2009 ◽  
Vol 20 (9) ◽  
pp. 1285-1298 ◽  
Author(s):  
S. Coll ◽  
F.J. Mora ◽  
J. Duato ◽  
F. Petrini
Keyword(s):  
Tree Networks ◽  
Scalable Hardware
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