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Modern Cooperative Parallel SAT Solving

14 pagesPublished: July 28, 2014


Nowadays, powerful parallel SAT solvers are based on an algorithm portfolio. The
alternative approach, (iterative) search space partitioning, cannot keep up, although, ac-
cording to the literature, iterative partitioning systems should scale better than portfolio
solvers. In this paper we identify key problems in current parallel cooperative SAT solving
approaches, most importantly communication, how to partition the search space, and how
to utilize the sequential search engine. First, we improve on each problem separately. In
a further step, we show that combining all the improvements leads to a state-of-the-art
parallel SAT solver, which does not use the portfolio approach, but instead relies on it-
erative partitioning. The experimental evaluation of this system completely changes the
picture about the performance of search space partitioning SAT solvers: on instances of
a combined benchmark of recent SAT competitions, the presented approach can keep up
with the winners of last years SAT competition. The combined improvements improve the
existing cooperative solver splitter by 24%: instead of 561 out of 880 instances, the new
solver Pcasso can solve 696 instances.

Keyphrases: clause sharing, cooperative parallelization, Iterative partitioning, look-ahead, parallel SAT solving, Search Space Splitting

In: Daniel Le Berre (editor). POS-13. Pragmatics of SAT 2013, vol 29, pages 41--54

BibTeX entry
  author    = {Norbert Manthey and Davide Lanti and Ahmed Irfan},
  title     = {Modern Cooperative Parallel SAT Solving},
  booktitle = {POS-13. Pragmatics of SAT 2013},
  editor    = {Daniel Le Berre},
  series    = {EPiC Series in Computing},
  volume    = {29},
  pages     = {41--54},
  year      = {2014},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2398-7340},
  url       = {},
  doi       = {10.29007/jnvf}}
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