Community and LBD-based Clause Sharing Policy for Parallel SAT Solving
From LRDE
- Authors
- Vincent Vallade, Ludovic Le Frioux, Souheib Baarir, Julien Sopena, Vijay Ganesh, Fabrice Kordon
- Where
- Proceedings of the 23rd International Conference on Theory and Applications of Satisfiability Testing (SAT'20)
- Type
- inproceedings
- Publisher
- Springer, Cham
- Keywords
- Parallel satisfiability, clause sharing, community structure
- Date
- 2020-06-01
Abstract
Modern parallel SAT solvers rely heavily on effective clause sharing policies for their performance. The core problem being addressed by these policies can be succinctly stated as "the problem of identifying high-quality learnt clauses" that when shared between the worker nodes of parallel solvers results in improved performance than otherwise. The term "high-quality clauses" is often defined in terms of metrics that solver designers have identified over years of empirical study. Some of the more well-known metrics to identify high-quality clauses for sharing include clause length, literal block distance (LBD), and clause usage in propagation. In this paper, we propose a new metric aimed at identifying high-quality learnt clauses and a concomitant clause-sharing policy based on a combination of LBD and community structure of Boolean formulas. The concept of community structure has been proposed as a possible explanation for the extraordinary performance of SAT solvers in industrial instances. Henceit is a natural candidate as a basis for a metric to identify high-quality clauses. To be more precise, our metric identifies clauses that have low LBD and low community number as ones that are high-quality for applications such as verification and testing. The community number of a clause C measures the number of different communities of a formula that the variables in C span. We perform extensive empirical analysis of our metric and clause-sharing policy, and show that our method significantly outperforms state-of-the-art techniques on the benchmark from the parallel track of the last four SAT competitions.
Documents
Bibtex (lrde.bib)
@InProceedings{ vallade.20.sat, author = {Vincent Vallade and Ludovic {Le Frioux} and Souheib Baarir and Julien Sopena and Vijay Ganesh and Fabrice Kordon}, title = {Community and {LBD}-based Clause Sharing Policy for Parallel {SAT} Solving}, booktitle = {Proceedings of the 23rd International Conference on Theory and Applications of Satisfiability Testing (SAT'20)}, year = 2020, doi = {10.1007/978-3-030-51825-7_2}, month = jun, volume = {12178}, pages = {11--27}, series = {Lecture Notes in Computer Science}, publisher = {Springer, Cham}, abstract = {Modern parallel SAT solvers rely heavily on effective clause sharing policies for their performance. The core problem being addressed by these policies can be succinctly stated as "the problem of identifying high-quality learnt clauses" that when shared between the worker nodes of parallel solvers results in improved performance than otherwise. The term "high-quality clauses" is often defined in terms of metrics that solver designers have identified over years of empirical study. Some of the more well-known metrics to identify high-quality clauses for sharing include clause length, literal block distance (LBD), and clause usage in propagation. In this paper, we propose a new metric aimed at identifying high-quality learnt clauses and a concomitant clause-sharing policy based on a combination of LBD and community structure of Boolean formulas. The concept of community structure has been proposed as a possible explanation for the extraordinary performance of SAT solvers in industrial instances. Hence, it is a natural candidate as a basis for a metric to identify high-quality clauses. To be more precise, our metric identifies clauses that have low LBD and low community number as ones that are high-quality for applications such as verification and testing. The community number of a clause C measures the number of different communities of a formula that the variables in C span. We perform extensive empirical analysis of our metric and clause-sharing policy, and show that our method significantly outperforms state-of-the-art techniques on the benchmark from the parallel track of the last four SAT competitions.} }