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.
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References
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)
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)
Marques-Silva, J.P., Lynce, I., Malik, S.: Conflict-driven clause learning SAT solvers. [41], 131–153
Marques-Silva, J.P., Sakallah, K.A.: GRASP: A search algorithm for propositional satisfiability. IEEE Trans. Computers 48(5), 506–521 (1999)
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
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)
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)
Ryan, L.: Efficient algorithms for clause-learning SAT solvers. Master’s thesis, Simon Fraser University (2004)
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
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)
Biere, A.: P\(\{\)re, i\(\}\)coSAT@SC 2009. In: SAT 2009 Competitive Event Booklet, pp. 42–43 (2009)
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)
Heule, M., van Maaren, H.: Look-ahead based SAT solvers. [41], 155–184
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)
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)
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)
Davis, M., Logemann, G., Loveland, D.W.: A machine program for theorem-proving. Commun. ACM 5(7), 394–397 (1962)
Bryant, R.E.: Graph-based algorithms for boolean function manipulation. IEEE Trans. Computers 35(8), 677–691 (1986)
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)
Jeroslow, R.G., Wang, J.: Solving propositional satisfiability problems. Annals of Mathematics and Artificial Intelligence 1(1–4), 167–187 (1990)
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)
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)
Zhang, H.: SATO: an efficient propositional prover. In: McCune, William (ed.) CADE 1997. LNCS, vol. 1249, pp. 272–275. Springer, Heidelberg (1997)
Biere, A.: PicoSAT essentials. JSAT 4(2–4), 75–97 (2008)
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)
Han, H., Somenzi, F.: On-the-fly clause improvement. In: Kullmann, O. (ed.) SAT 2009. LNCS, vol. 5584, pp. 209–222. Springer, Heidelberg (2009)
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
van der Tak, P., Ramos, A., Heule, M.J.H.: Reusing the assignment trail in CDCL solvers. JSAT 7(4), 133–138 (2011)
Nadel, A.: Backtrack search algorithms for propositional logic satisfiability: Review and innovations. Master’s thesis, Hebrew University (2002)
Sleator, D.D., Tarjan, R.E.: Amortized efficiency of list update and paging rules. Commun. ACM 28(2), 202–208 (1985)
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)
Biere, A.: Yet another local search solver and Lingeling and friends entering the SAT Competition 2014. [2], 39–40
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
Audemard, G., Simon, L.: Glucose 2.3 in the SAT 2013 Competition. [1], 42–43
Oh, C.: MiniSat HACK 999ED, MiniSat HACK 1430ED and SWDiA5BY. [2], 46–47
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)
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)
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)
Wallner, J.P.: Benchmark for complete and stable semantics for argumentation frameworks. [2], 84–85
Biere, A., Heule, M.J.H., Järvisalo, M., Manthey, N.: Equivalence checking of HWMCC 2012 circuits. [1], 104
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)
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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
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