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From Sequential to Parallel Local Search for SAT

  • Alejandro Arbelaez
  • Philippe Codognet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7832)

Abstract

In the domain of propositional Satisfiability Problem (SAT), parallel portfolio-based algorithms have become a standard methodology for both complete and incomplete solvers. In this methodology several algorithms explore the search space in parallel, either independently or cooperatively with some communication between the solvers. We conducted a study of the scalability of several SAT solvers in different application domains (crafted, verification, quasigroups and random instances) when drastically increasing the number of cores in the portfolio, up to 512 cores. Our experiments show that on different problem families the behaviors of different solvers vary greatly. We present an empirical study that suggests that the best sequential solver is not necessary the one with the overall best parallel speedup.

Keywords

Local Search Local Search Algorithm Random Instance Parallel Local Core Increase 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alejandro Arbelaez
    • 1
  • Philippe Codognet
    • 2
    • 3
  1. 1.JFLIUniversity of TokyoJapan
  2. 2.JFLI - CNRS / UPMCUniversity of TokyoJapan
  3. 3.Dept. of Computer ScienceUniversity of TokyoBunkyo-kuJapan

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