Predicting SAT Solver Performance on Heterogeneous Hardware

16 pages•Published: March 15, 2019

Zack Newsham, Vijay Ganesh and Sebastian Fischmeister

Abstract

In recent years, a lot of effort has been expended in determining if SAT solver performance is predictable. However, the work in this area invariably focuses on individual machines, and often on individual solvers. It is unclear whether predictions made on a specific solver and machine are accurate when translated to other solvers and hardware. In this work we consider five state-of-the-art solvers, 26 machines and 143 feature instances selected from the 2011 to 2014 SAT competitions. Using combinations of solvers, machines and instances we present four results: First, we show that UNSAT instances are more predictable than corresponding SAT instances. Second, we show that the number of cores in a machine has more impact on performance than L2 cache size. Third, we show that instances with fewer reused clauses are more CPU bound than those where clause reuse is high. Finally, we make accurate predictions of solution time for each of the instances considered across a diverse set of machines.

In: Daniel Le Berre and Matti Järvisalo (editors). Proceedings of Pragmatics of SAT 2015 and 2018, vol 59, pages 18-33.

Links:	https://easychair.org/publications/paper/s7wG
	https://doi.org/10.29007/8m31

BibTeX entry

@inproceedings{POS-18:Predicting_SAT_Solver_Performance,
  author    = {Zack Newsham and Vijay Ganesh and Sebastian Fischmeister},
  title     = {Predicting SAT Solver Performance on Heterogeneous Hardware},
  booktitle = {Proceedings of Pragmatics of SAT 2015 and 2018},
  editor    = {Daniel Le Berre and Matti Järvisalo},
  series    = {EPiC Series in Computing},
  volume    = {59},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/s7wG},
  doi       = {10.29007/8m31},
  pages     = {18-33},
  year      = {2019}}

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