Study of Fine-grained Nested Parallelism in CDCL SAT Solvers

Author:

Edwards James1,Vishkin Uzi1

Affiliation:

1. University of Maryland, Maryland, USA

Abstract

Boolean satisfiability (SAT) is an important performance-hungry problem with applications in many problem domains. However, most work on parallelizing SAT solvers has focused on coarse-grained, mostly embarrassing, parallelism. Here, we study fine-grained parallelism that can speed up existing sequential SAT solvers, which all happen to be of the so-called Conflict-Directed Clause Learning variety. We show the potential for speedups of up to 382× across a variety of problem instances. We hope that these results will stimulate future research, particularly with respect to a computer architecture open problem we present.

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Modeling and Simulation,Software

Reference59 articles.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Empirical Challenge for NC Theory (Abstract);Proceedings of the 2023 ACM Workshop on Highlights of Parallel Computing;2023-07-18

2. Beyond worst-case analysis;Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores;2022-04-02

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