6941919
Optimizations for Compiling Declarative Models into Boolean Formulas
Advances in SAT solver technology have enabled many automated analysis and reasoning tools to reduce their input problem to a SAT problem, and then to use an efficient SAT solver to solve the underlying analysis or reasoning problem. The solving time for SAT solvers can vary substantially for semantically identical SAT problems depending on how the problem is expressed. This property motivates the development of new optimization techniques whose goal is to produce more efficiently solvable SAT problems, thereby improving the overall performance of the analysis or reasoning tool. 
 
This paper presents our experience using several mechanical techniques that enable the Alloy Analyzer to generate optimized SAT formulas from first-order logic formulas. These techniques are inspired by similar techniques from the field of optimizing compilers, suggesting the potential presence of underlying connections between optimization problems from two very different domains. Our experimental results show that our techniques can deliver substantial performance improvement results—in some cases, they reduce the solving time by an order of magnitude.
18035076
On Subsumption Removal and On-the-Fly CNF Simplification
CNF Boolean formulas generated from resolution or solution enumeration often have much redundancy. Efficient algorithms are needed to simplify and compact such CNF formulas. In this paper, we present a novel algorithm to maintain a subsumption-free CNF clause database by efficiently detecting and removing subsumption as the clauses are being added. We then present an algorithm that compact CNF formula further by applying resolutions to make it Decremental Resolution Free. Our experimental evaluations show that these algorithms are efficient and effective in practice.
9292941
Chaff: engineering an efficient SAT solver
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.
6734525
Propositional Satisfiability and Constraint Programming: A comparative survey
Propositional Satisfiability (SAT) and Constraint Programming (CP) have developed as two relatively independent threads of research cross-fertilizing occasionally. These two approaches to problem solving have a lot in common as evidenced by similar ideas underlying the branch and prune algorithms that are most successful at solving both kinds of problems. They also exhibit differences in the way they are used to state and solve problems since SAT's approach is, in general, a black-box approach, while CP aims at being tunable and programmable. This survey overviews the two areas in a comparative way, emphasizing the similarities and differences between the two and the points where we feel that one technology can benefit from ideas or experience acquired from the other.
14923930
Cache Performance of SAT Solvers: a Case Study for Efficient Implementation of Algorithms
We experimentally evaluate the cache performance of different SAT solvers as a case study for the efficient implementation of SAT algorithms. We evaluate several different Boolean Constraint Propagation (BCP) mechanisms and show their respective run time and cache performances on selected benchmark instances. From the experiments we conclude that a cache friendly data structure is a key element in the efficient implementation of SAT solvers. We also show empirical cache miss rates of several modern SAT solvers based on the Davis-Logemann-Loveland (DLL) algorithm with learning and non-chronological backtracking. We conclude that the recently developed SAT solvers are much more cache friendly in data structures and algorithm implementations compared with their predecessors.
11375306
A solver for quantified Boolean and linear constraints
We make a number of contributions to the understanding and practical resolution of quantified constraints. Unlike previous work in the CP literature that was essentially focused on constraints expressed as binary tables, we focus on Presburger Arithmetics, i.e., Boolean combinations of linear constraints. From a theoretical perspective, we clarify the problem of the treatment of universal quantifiers by proposing a "symmetric" version of the notion of quantified consistency. This notion imposes to maintain two constraint stores, which will be used to reason on universal and existential variables, respectively. We then describe a branch & bound algorithm that integrates both forms of propagation. Its implementation is, to the best of our knowledge, the first CP solver for this class of quantified constraints.
36054855
MQML-Message Queuing Markup Language
Message Queuing allows applications to use components that communicate with one another using queued messages. In this paper, we propose a Message Queuing Markup Language (MQML), which is an XML based markup language designed to describe e-business applications and enterprise integration. The MQML language is extensible. The detailed description of the MQML is presented in this paper. An research prototype is given to validate the effectiveness and value of our proposed MQML for enterprise integration.
6040398
C-DIST: efficient distance computation for rigid and articulated models in configuration space
The problem of distance computation arises in many applications including motion planning, CAD/CAM, dynamic simulation and virtual environments. Most prior work in this area has been restricted to separation or penetration distance computation between two objects. In this paper, we address the problem of computing a measure of distance between two configurations of a rigid or articulated model. The underlying distance metric is defined as the length of the longest displacement vector over the corresponding vertices of the model between two configurations. Our algorithm is based on Chasles theorem in Screw theory, and we show that the maximum distance can be realized only by a vertex of the convex hull of a rigid object. We use this formulation to compute the distance, and present two acceleration techniques to speed up the computation: incremental walking on the dual space of the convex hull and culling vertices on the convex hull using a bounding volume hierarchy (BVH). Our algorithm can be easily extended to articulated models by maximizing the distance over its each link and we also present culling techniques to accelerate the computation. We highlight the performance of our algorithm on many complex models and describe its application to proximity queries and motion planning.
14861274
Learning in Region-Based Image Retrieval
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to regionbased image retrieval (RBIR). First, the query point movement technique is considered. By assembling all the segmented regions of positive examples together and resizing the regions to emphasize the latest positive examples, a composite image is formed as the new query. Second, the application of support vector machines (SVM) in relevance feedback for RBIR is investigated. Both the one class SVM as a class distribution estimator and two classes SVM as a classifier are taken into account. For the latter, two representative display strategies are studied. Last, a region re-weighting algorithm is proposed inspired by those feature re-weighting ones. Experimental results on a database of 10,000 general-purpose images demonstrate the effectiveness of the proposed learning algorithms.
14817235
Placement Algorithm in Analog-Layout Designs
Analog macrocell placement is an NP-hard problem. This paper presents an attempt to solve this problem by using the optimization flow of a genetic algorithm (GA) enhanced by simulated annealing (SA). The bit-matrix representation is employed to improve the search efficiency. In particular, to reduce the solution space without degrading search opportunities, the technique of cell slide is deployed to transform an absolute placement to a relative placement. Following this cell-slide process, it is proved that, for an initial placement, there always exists a solution that can guarantee no occurrence of overlaps among cells and meet any applicable symmetry constraints pertaining to analog layouts. For the optimization of the algorithm parameters, the fractional factorial experiment using an orthogonal array has been conducted, and the exact parameter values are determined using a meta-GA approach. The experimental results show that, compared with the SA approach, the proposed algorithm consumes less computation time while generating higher quality layouts, comparable to expert manual placements
34237375
On-Demand Business Collaboration Enablement with Services Computing
In this talk, I will introduce a model for on-demand business process based collaboration, namely, Extended Business Collaboration (eBC), and its major characteristics: modeling, solution stack, configurable business protocol enabling framework, on-demand services deployment, as well as monitoring and analytical control. Then we present a few major research issues associated with facilitating extended business collaboration, followed by our proposed Annotated Business HyperChain technology leveraging Services computing and semantic annotation model. Services computing is the evolution of Internet computing by leveraging services oriented architecture. Services computing is mainly targeting for a new ground break technology suite – Web services and services oriented Grid/Utility Computing, Business Computing, and Autonomic Computing. A research prototype is illustrated at the end of the talk followed by some observations and discussion of open research issues requiring further exploration.