Skip to main content

Evaluating CDCL Variable Scoring Schemes

  • Conference paper
  • First Online:
Theory and Applications of Satisfiability Testing -- SAT 2015 (SAT 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9340))

Abstract

The VSIDS (variable state independent decaying sum) decision heuristic invented in the context of the CDCL (conflict-driven clause learning) SAT solver Chaff, is considered crucial for achieving high efficiency of modern SAT solvers on application benchmarks. This paper proposes ACIDS (average conflict-index decision score), a variant of VSIDS. The ACIDS heuristics is compared to the original implementation of VSIDS, its popular modern implementation EVSIDS (exponential VSIDS), the VMTF (variable move-to-front) scheme, and other related decision heuristics. They all share the important principle to select those variables as decisions, which recently participated in conflicts. The main goal of the paper is to provide an empirical evaluation to serve as a starting point for trying to understand the reason for the efficiency of these decision heuristics. In our experiments, it turns out that EVSIDS, VMTF, ACIDS behave very similarly, if implemented carefully.

Supported by Austrian Science Fund (FWF), national research network RiSE (S11408-N23). Builds on discussions from the 2014 workshop on Theoretical Foundations of Applied SAT Solving (14w5101), hosted by Banff International Research Station, and Dagstuhl Seminar 15171 (2015), Theory and Practice of SAT Solving.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Balint, A., Belov, A., Heule, M.J.H., Järvisalo, M. (eds.): Proceedings of SAT Competition 2013. Volume B-2013-1 of Department of Computer Science Series of Publications B. University of Helsinki (2013)

    Google Scholar 

  2. Belov, A., Heule, M.J.H., Järvisalo, M. (eds.): Proceedings of SAT Competition 2014. Volume B-2014-2 of Department of Computer Science Series of Publications B. University of Helsinki (2014)

    Google Scholar 

  3. Marques-Silva, J.P., Lynce, I., Malik, S.: Conflict-driven clause learning SAT solvers. [41], 131–153

    Google Scholar 

  4. Marques-Silva, J.P., Sakallah, K.A.: GRASP: A search algorithm for propositional satisfiability. IEEE Trans. Computers 48(5), 506–521 (1999)

    Article  MathSciNet  Google Scholar 

  5. Moskewicz, M.W., Madigan, C.F., Zhao, Y., Zhang, L., Malik, S.: Chaff: engineering an efficient SAT solver. In: Proceedings of the 38th Design Automation Conference, DAC 2001, pp. 530–535. ACM, Las Vegas, June 18–22, 2001

    Google Scholar 

  6. Biere, A.: Adaptive restart strategies for conflict driven SAT solvers. In: Kleine Büning, H., Zhao, X. (eds.) SAT 2008. LNCS, vol. 4996, pp. 28–33. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Eén, N., Sörensson, N.: An extensible SAT-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Ryan, L.: Efficient algorithms for clause-learning SAT solvers. Master’s thesis, Simon Fraser University (2004)

    Google Scholar 

  9. Goldberg, E.I., Novikov, Y.: Berkmin: a fast and robust sat-solver. In: 2002 Design, Automation and Test in Europe Conference and Exposition (DATE 2002), pp. 142–149. IEEE Computer Society, Paris, March 4–8, 2002

    Google Scholar 

  10. Gershman, R., Strichman, O.: Haifasat: A new robust SAT solver. In: Ur, S., Bin, E., Wolfsthal, Y. (eds.) Hardware and Software Verification and Testing. LNCS, vol. 3875, pp. 76–89. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Biere, A.: P\(\{\)re, i\(\}\)coSAT@SC 2009. In: SAT 2009 Competitive Event Booklet, pp. 42–43 (2009)

    Google Scholar 

  12. Heule, M.J.H., Kullmann, O., Wieringa, S., Biere, A.: Cube and conquer: guiding CDCL SAT solvers by lookaheads. In: Eder, K., Lourenço, J., Shehory, O. (eds.) HVC 2011. LNCS, vol. 7261, pp. 50–65. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  13. Heule, M., van Maaren, H.: Look-ahead based SAT solvers. [41], 155–184

    Google Scholar 

  14. Ansótegui, C., Giráldez-Cru, J., Levy, J.: The community structure of SAT formulas. In: Cimatti, A., Sebastiani, R. (eds.) SAT 2012. LNCS, vol. 7317, pp. 410–423. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  15. Newsham, Z., Ganesh, V., Fischmeister, S., Audemard, G., Simon, L.: Impact of community structure on SAT solver performance. In: Sinz, C., Egly, U. (eds.) SAT 2014. LNCS, vol. 8561, pp. 252–268. Springer, Heidelberg (2014)

    Google Scholar 

  16. Ansótegui, C., Bonet, M.L., Giráldez-Cru, J., Levy, J.: The fractal dimension of SAT formulas. In: Demri, S., Kapur, D., Weidenbach, C. (eds.) IJCAR 2014. LNCS, vol. 8562, pp. 107–121. Springer, Heidelberg (2014)

    Google Scholar 

  17. Davis, M., Logemann, G., Loveland, D.W.: A machine program for theorem-proving. Commun. ACM 5(7), 394–397 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  18. Bryant, R.E.: Graph-based algorithms for boolean function manipulation. IEEE Trans. Computers 35(8), 677–691 (1986)

    Article  MATH  Google Scholar 

  19. Biere, A., Cimatti, A., Clarke, E., Zhu, Y.: Symbolic model checking without BDDs. In: Cleaveland, W.R. (ed.) TACAS 1999. LNCS, vol. 1579, p. 193. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  20. Jeroslow, R.G., Wang, J.: Solving propositional satisfiability problems. Annals of Mathematics and Artificial Intelligence 1(1–4), 167–187 (1990)

    Article  MATH  Google Scholar 

  21. Marques-Silva, J.: The impact of branching heuristics in propositional satisfiability algorithms. In: Barahona, P., Alferes, J.J. (eds.) EPIA 1999. LNCS (LNAI), vol. 1695, pp. 62–74. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  22. Pipatsrisawat, K., Darwiche, A.: A lightweight component caching scheme for satisfiability solvers. In: Marques-Silva, J., Sakallah, K.A. (eds.) SAT 2007. LNCS, vol. 4501, pp. 294–299. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  23. Zhang, H.: SATO: an efficient propositional prover. In: McCune, William (ed.) CADE 1997. LNCS, vol. 1249, pp. 272–275. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  24. Biere, A.: PicoSAT essentials. JSAT 4(2–4), 75–97 (2008)

    MATH  Google Scholar 

  25. Beame, P., Kautz, H.A., Sabharwal, A.: Towards understanding and harnessing the potential of clause learning. J. Artif. Intell. Res. (JAIR) 22, 319–351 (2004)

    MathSciNet  MATH  Google Scholar 

  26. Han, H., Somenzi, F.: On-the-fly clause improvement. In: Kullmann, O. (ed.) SAT 2009. LNCS, vol. 5584, pp. 209–222. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  27. Hamadi, Y., Jabbour, S., Sais, L.: Learning for dynamic subsumption. In: 21st IEEE International Conference on Tools with Artificial Intelligence, Newark, New Jersey, USA, ICTAI 2009, pp. 328–335. IEEE Computer Society, November 2–4, 2009

    Google Scholar 

  28. van der Tak, P., Ramos, A., Heule, M.J.H.: Reusing the assignment trail in CDCL solvers. JSAT 7(4), 133–138 (2011)

    MathSciNet  MATH  Google Scholar 

  29. Nadel, A.: Backtrack search algorithms for propositional logic satisfiability: Review and innovations. Master’s thesis, Hebrew University (2002)

    Google Scholar 

  30. Sleator, D.D., Tarjan, R.E.: Amortized efficiency of list update and paging rules. Commun. ACM 28(2), 202–208 (1985)

    Article  MathSciNet  Google Scholar 

  31. Biere, A.: Lingeling and friends entering the SAT challenge 2012. In: Balint, A., Belov, A., Diepold, D., Gerber, S., Järvisalo, M., Sinz, C. (eds.) Proceedings SAT Challenge 2012: Solver and Benchmark Descriptions. Volume B-2012-2 of Department of Computer Science Series of Publications B., University of Helsinki, pp. 33–34 (2012)

    Google Scholar 

  32. Biere, A.: Yet another local search solver and Lingeling and friends entering the SAT Competition 2014. [2], 39–40

    Google Scholar 

  33. Audemard, G., Simon, L.: Predicting learnt clauses quality in modern SAT solvers. In: Boutilier, C. (ed.) Proceedings of the 21st International Joint Conference on Artificial Intelligence, IJCAI 2009, Pasadena, California, USA, pp. 399–404, July 11–17, 2009

    Google Scholar 

  34. Audemard, G., Simon, L.: Glucose 2.3 in the SAT 2013 Competition. [1], 42–43

    Google Scholar 

  35. Oh, C.: MiniSat HACK 999ED, MiniSat HACK 1430ED and SWDiA5BY. [2], 46–47

    Google Scholar 

  36. Järvisalo, M., Heule, M.J.H., Biere, A.: Inprocessing rules. In: Gramlich, B., Miller, D., Sattler, U. (eds.) IJCAR 2012. LNCS, vol. 7364, pp. 355–370. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  37. Audemard, G., Simon, L.: Refining restarts strategies for SAT and UNSAT. In: Milano, M. (ed.) CP 2012. LNCS, vol. 7514, pp. 118–126. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  38. Eén, N., Biere, A.: Effective preprocessing in SAT through variable and clause elimination. In: Bacchus, F., Walsh, T. (eds.) SAT 2005. LNCS, vol. 3569, pp. 61–75. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  39. Wallner, J.P.: Benchmark for complete and stable semantics for argumentation frameworks. [2], 84–85

    Google Scholar 

  40. Biere, A., Heule, M.J.H., Järvisalo, M., Manthey, N.: Equivalence checking of HWMCC 2012 circuits. [1], 104

    Google Scholar 

  41. Biere, A., Heule, M.J.H., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability. Volume 185 of Frontiers in Artificial Intelligence and Applications. IOS Press (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Armin Biere .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Biere, A., Fröhlich, A. (2015). Evaluating CDCL Variable Scoring Schemes. In: Heule, M., Weaver, S. (eds) Theory and Applications of Satisfiability Testing -- SAT 2015. SAT 2015. Lecture Notes in Computer Science(), vol 9340. Springer, Cham. https://doi.org/10.1007/978-3-319-24318-4_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-24318-4_29

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24317-7

  • Online ISBN: 978-3-319-24318-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics