Variable ordering for shared binary decision diagrams targeting node count and path length optimisation using particle swarm technique
Variable ordering for shared binary decision diagrams targeting node count and path length optimisation using particle swarm technique
- Author(s): A. Mitra and S. Chattopadhyay
- DOI: 10.1049/iet-cdt.2011.0051
For access to this article, please select a purchase option:
Buy article PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
Thank you
Your recommendation has been sent to your librarian.
- Author(s): A. Mitra 1 and S. Chattopadhyay 1
-
-
View affiliations
-
Affiliations:
1: Department of Electronics and Electrical Communication Engineering, IIT Kharagpur, Kharagpur, India
-
Affiliations:
1: Department of Electronics and Electrical Communication Engineering, IIT Kharagpur, Kharagpur, India
- Source:
Volume 6, Issue 6,
November 2012,
p.
353 – 361
DOI: 10.1049/iet-cdt.2011.0051 , Print ISSN 1751-8601, Online ISSN 1751-861X
- « Previous Article
- Table of contents
- Next Article »
This study presents a particle swarm optimisation (PSO)-based approach to optimise node count and path length of the binary decision diagram (BDD) representation of Boolean function. The optimisation is achieved by identifying a good ordering of the input variables of the function. This affects the structure of the resulting BDD. Both node count and longest path length of the shared BDDs using the identified input ordering are found to be much superior to the existing results. The improvements are more prominent for larger benchmarks. The PSO parameters have been tuned suitably to explore a large search space within a reasonable computation time.
Inspec keywords: search problems; directed graphs; particle swarm optimisation; binary decision diagrams
Other keywords:
Subjects: Optimisation; Algebra, set theory, and graph theory; Combinatorial mathematics; Optimisation techniques; Combinatorial mathematics; Optimisation techniques; Combinatorial mathematics
References
-
-
1)
- F. Somenzi . CUDD: CU decision diagram package.
-
2)
- M. Raseen , K. Thanduki . ROBDD optimization using sub graph complexity. Int. J. Comput. Sci. Netw. Secur. , 8 , 137 - 145
-
3)
- Deharbe, D., Vidal, J.M.B.: `Optimizing BDD-based verification analyzing variable dependencies', Proc. 14th Symp. Integrated Circuits and Systems Design, 2001, p. 64–69.
-
4)
- Eberhart, R.C., Shi, Y.: `Particle swarm optimization: developments, applications and resources', Proc. Congress on Evolutionary Computation, 2001, p. 81–86.
-
5)
- J.L. Nielsen . Buddy-a binary decision diagram package.
-
6)
- Rudell, R.: `Dynamic variable ordering for ordered binary decision diagrams', Proc. IEEE/ACM Int. Conf. Computer-Aided Design, 1993, p. 42–47.
-
7)
- Du, S., Sun, Y.: `Comparison of progressive variable ordering methods with fixed ordering heuristics for binary decision diagrams', Proc. Wireless Communications, Networking and Mobile Computing, 2007, p. 4581–4584.
-
8)
- M. Fujita , H. Fujisawa , Y. Matsunaga . Variable ordering algorithms for ordered binary decision diagrams and their evaluation. IEEE Trans. Comput. Aided Des. , 1 , 6 - 12
-
9)
- Chaudhury, S., Chattopadhyay, S.: `Output phase assignment for area and power optimization in multi-level multi-output combinational logic circuits', Annual IEEE India Conf., 2006, p. 15–17.
-
10)
- Malik, S., Wang, A.R., Brayton, R.K., Sangiovanni-Vincentelli, A.: `Logic verification using binary decision diagrams in a logic synthesis environment', Int. Conf. Computer Aided Design, 1988, p. 6–9.
-
11)
- Aloul, F.A., Markov, I.L., Sakallah, K.A.: `Faster SAT and smaller BDDs via common function structure', Proc. Int. Conf. Computer Aided Design, 2001, p. 443–448.
-
12)
- Nagayama, S., Mishchenko, A., Sasao, T., Butler, J.T.: `Minimization of average path length in BDDs by variable reordering', Int. Workshop on Logic and Synthesis, 2007, p. 207–213.
-
13)
- F. Balarin , M. Chiodo , P. Guisto . Synthesis of software programs for embedded control applications. IEEE Trans. Comput. Aided Des. , 6 , 834 - 849
-
14)
- R. Drechsler , R. Becker , N. Gockel . Genetic algorithm for variable ordering of OBDDs. IEE Proc. Comput. Digit. Tech. , 6 , 364 - 368
-
15)
- M. Raseen , A. Assi . BDD path length minimization based on initial variable ordering. J. Comput. Sci. , 4 , 521 - 529
-
16)
- R. Poli , J. Kennedy , T. Blackwell . (2007) Particle swarm optimization: an overview.
-
17)
- Nagayama, S., Sasao, T.: `On the minimization of longest path length for decision diagrams', Int. Workshop on Logic and Synthesis, 2004, p. 28–35.
-
18)
- R.E. Bryant . Graph-based algorithms for Boolean function manipulation. IEEE Trans. Comput. , 8 , 677 - 691
-
19)
- T.I. Cristian . The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf. Process. Lett. , 6 , 317 - 325
-
20)
- Kennedy, J.: `The particle swarm: social adaptation of knowledge', Proc. IEEE Int. Conf. Evolutionary Computation, 1997, p. 303–308.
-
21)
- Hassan, R., Cohanim, B., Weck, O.D.: `A comparison of particle swarm optimization and the genetic algorithm', First AIAA Multidisciplinary Design Optimization Specialist Conf., 2005, Austin.
-
22)
- M. Rice , S. Kulhari . (2009) A survey of static variable ordering heuristics for efficient BDD/MDD construction.
-
23)
- Drechsler, R.: `Evaluation of static variable ordering heuristics for MDD construction', Int. Symp. Multi-valued Logic, 2002, p. 254–260.
-
24)
- Brace, K.S., Rudell, R.L., Bryant, R.E.: `Efficient implementation of a BDD package', Twenty-seventh ACM/IEEE Design Automation Conf., 1990.
-
25)
- P.W.C. Prasad , A. Assi , A. Harb , V.C. Prasad . Binary decision diagrams: an improved variable ordering using graph representation of Boolean functions. Int. J. Electr. Comput. Eng. , 1 , 1 - 7
-
26)
- R. Drechsler . Verification of multi-valued logic networks. Mult.-Valued Log. – Int. J. , 1 , 77 - 88
-
27)
- B. Bollig , I. Wegener . Improving the variable ordering of OBDDs is NP-complete. IEEE Trans. Comput. , 9 , 993 - 1002
-
28)
- S.B. Akers . Binary decision diagrams. IEEE Trans. Comput. , 6 , 509 - 516
-
29)
- C.M. Fonseca , P.J. Fleming . An overview of evolutionary algorithms in multiple objectives optimisation. Evol. Comput. , 1 , 1 - 16
-
30)
- Fujii, H., Ootomo, G., Hori, C.: `Interleaving based variable ordering algorithms for ordered binary decision diagrams', Int. Conf. Computer Aided Design, 1993, p. 38–41.
-
1)
Related content
