Volume 8 Number 11 (Nov. 2013)
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JSW 2013 Vol.8(11): 2770-2774 ISSN: 1796-217X
doi: 10.4304/jsw.8.11.2770-2774

Optimisation of Mixed Polarity Reed-Muller Functions

Meng Yang, Jinmei Lai
State Key Lab of ASIC and System, Fudan University, Shanghai, China

Abstract—This paper presents a genetic algorithm (GA) search method in order to obtain better circuit implementation of the mixed polarity Reed-Muller functions. By combining global searching ability of genetic algorithm and local searching ability of simulated annealing, the proposed GA method could achieve fast convergence. It differs to traditional genetic algorithm, in which the proposed GA forms an intermediate population by using 2/3 population from previous generation and 2/3 population from current generation at the annealing stage. Annealing is then applied to the intermediate population to generate a new population. In the next generation selection, crossover and mutation operations are used for the newly generated population. The calculation of cost function of proposed algorithm is based on parallel tabular technique to overcome the disadvantage of the traditional tabular technique. The results of the tested benchmark indicated that this algorithm is highly effective for searching the best polarity and it could achieve 29% area reduction and 3.68X speedup.

Index Terms—Logic synthesis, Reed-Muller, mixed polarity, genetic algorithm, computer aided design.


Cite: Meng Yang, Jinmei Lai, "Optimisation of Mixed Polarity Reed-Muller Functions," Journal of Software vol. 8, no. 11, pp. 2770-2774, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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