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文献详情 >A Locating Method for Reliabil... 收藏

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

作     者:Jie Xiao Zhan-Hui Shi Jian-Hui Jiang Xu-Hua Yang Yu-Jiao Huang Hai-Gen Hu 

作者机构:College of Computer Science and TechnologyZhejiang University of TechnologyHangzhou 310023China School of Software EngineeringTongji UniversityShanghai 201804China 

出 版 物:《Journal of Computer Science & Technology》 (计算机科学技术学报(英文版))

年 卷 期:2019年第34卷第5期

页      面:1136-1151页

核心收录:

学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

基  金:supported by the National Natural Science Foundation of China under Grant Nos. 61972354,61502422,61432017, 61772199,61773348,and 61503338 the Natural Science Foundation of Zhejiang Province of China under Grant Nos. LY18F020028 LY18F030023,LY18F030084,and LY17F030016 and the Innovative Experiment Project of Zhejiang University of Technology of China under Grant No. PX-68182112 

主  题:gate-level circuit reliability locating reliability-critical gate parallel-structured genetic algorithm directing strategy scoring mechanism 

摘      要: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.

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