A Locating Method for Reliability-Critical Gates with a Parallel-Structured Genetic Algorithm

The reliability allowance of circuits tends to decrease with the increase of circuit integration and the application of new technology and materials, and the hardening strategy oriented toward gates is an effective technology for improving the circuit reliability of the current situations. Therefore...

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Published in:	Journal of computer science and technology Vol. 34; no. 5; pp. 1136 - 1151
Main Authors:	Xiao, Jie, Shi, Zhan-Hui, Jiang, Jian-Hui, Yang, Xu-Hua, Huang, Yu-Jiao, Hu, Hai-Gen
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.09.2019 Springer Nature B.V College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China%School of Software Engineering, Tongji University, Shanghai 201804, China
Subjects:	Artificial Intelligence Binary codes Circuit reliability Computer Science Convergence Data Structures and Information Theory Gates (circuits) Genetic algorithms Hardening Identification methods Information Systems Applications (incl.Internet) New technology Optimization Parallel operation Regular Paper Software Engineering Theory of Computation locating reliability-critical gate scoring mechanism gate-level circuit reliability directing strategy parallel-structured genetic algorithm
ISSN:	1000-9000, 1860-4749
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Abstract	The reliability allowance of circuits tends to decrease with the increase of circuit integration and the application of new technology and materials, and the hardening strategy oriented toward gates is an effective technology for improving the circuit reliability of the current situations. Therefore, a parallel-structured genetic algorithm (GA), PGA, is proposed in this paper to locate reliability-critical gates to successfully perform targeted hardening. Firstly, we design a binary coding method for reliability-critical gates and build an ordered initial population consisting of dominant individuals to improve the quality of the initial population. Secondly, we construct an embedded parallel operation loop for directional crossover and directional mutation to compensate for the deficiency of the poor local search of the GA. Thirdly, for combination with a diversity protection strategy for the population, we design an elitism retention based selection method to boost the convergence speed and avoid being trapped by a local optimum. Finally, we present an ordered identification method oriented toward reliability-critical gates using a scoring mechanism to retain the potential optimal solutions in each round to improve the robustness of the proposed locating method. The simulation results on benchmark circuits show that the proposed method PGA is an efficient locating method for reliability-critical gates in terms of accuracy and convergence speed.
AbstractList	The reliability allowance of circuits tends to decrease with the increase of circuit integration and the application of new technology and materials, and the hardening strategy oriented toward gates is an effective technology for improving the circuit reliability of the current situations. Therefore, a parallel-structured genetic algorithm (GA), PGA, is proposed in this paper to locate reliability-critical gates to successfully perform targeted hardening. Firstly, we design a binary coding method for reliability-critical gates and build an ordered initial population consisting of dominant individuals to improve the quality of the initial population. Secondly, we construct an embedded parallel operation loop for directional crossover and directional mutation to compensate for the deficiency of the poor local search of the GA. Thirdly, for combination with a diversity protection strategy for the population, we design an elitism retention based selection method to boost the convergence speed and avoid being trapped by a local optimum. Finally, we present an ordered identification method oriented toward reliability-critical gates using a scoring mechanism to retain the potential optimal solutions in each round to improve the robustness of the proposed locating method. The simulation results on benchmark circuits show that the proposed method PGA is an efficient locating method for reliability-critical gates in terms of accuracy and convergence speed.
Author	Xiao, Jie Yang, Xu-Hua Jiang, Jian-Hui Hu, Hai-Gen Huang, Yu-Jiao Shi, Zhan-Hui
AuthorAffiliation	College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China%School of Software Engineering, Tongji University, Shanghai 201804, China
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Cites_doi	10.1016/j.ejor.2017.07.027 10.1016/j.microrel.2010.07.154 10.1109/TC.2012.276 10.1109/TVLSI.2015.2442260 10.1109/TC.2015.2458868 10.1109/TMTT.2017.2672544 10.1109/ACCESS.2018.2845911 10.1109/TR.2016.2642168 10.1109/TPDS.2015.2426179 10.1016/j.ress.2012.08.003 10.1016/j.mejo.2016.03.013 10.1016/j.ress.2009.09.001 10.1109/TCAD.2017.2695881 10.1109/TEVC.2017.2753538 10.1109/ACCESS.2018.2800712 10.1109/TVLSI.2012.2208130 10.1155/1996/75798 10.1038/nature16961 10.1007/978-81-322-2752-6_72 10.1109/NEWCAS.2009.5290448 10.1002/9781118631980 10.1007/978-3-319-22053-6_1 10.1109/TR.2019.2897455
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Snippet	The reliability allowance of circuits tends to decrease with the increase of circuit integration and the application of new technology and materials, and the...
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SubjectTerms	Artificial Intelligence Binary codes Circuit reliability Computer Science Convergence Data Structures and Information Theory Gates (circuits) Genetic algorithms Hardening Identification methods Information Systems Applications (incl.Internet) New technology Optimization Parallel operation Regular Paper Software Engineering Theory of Computation
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Title	A Locating Method for Reliability-Critical Gates with a Parallel-Structured Genetic Algorithm
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