A Power and Area Optimization Approach of Mixed Polarity Reed-Muller Expression for Incompletely Specified Boolean Functions

doi:10.1007/s11390-017-1723-1

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	A Power and Area Optimization Approach of Mixed Polarity Reed-Muller Expression for Incompletely Specified Boolean Functions
	He, Zhen-Xue 2,3; Xiao, Li -Min 2,3; Ruan, Li 2,3; Gu, Fei 3; Huo, Zhi-Sheng 2,3; Qin, Guang-Jun 4; Zhu, Ming-Fa 2,3; Zhang, Long-Bing 1,5; Liu, Rui 4,6; Wang, Xiang 4
刊名	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
	2017-03-01
卷号	32 期号:2 页码:297-311
关键词	power and area optimization Reed-Muller (RM) circuit Pareto optimal solution don't care term chromosome conversion
ISSN号	1000-9000
DOI	10.1007/s11390-017-1723-1
英文摘要	The power and area optimization of Reed-Muller (RM) circuits has been widely concerned. However, almost none of the exiting power and area optimization approaches can obtain all the Pareto optimal solutions of the original problem and are efficient enough. Moreover, they have not considered the don't care terms, which makes the circuit performance unable to be further optimized. In this paper, we propose a power and area optimization approach of mixed polarity RM expression (MPRM) for incompletely specified Boolean functions based on Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Firstly, the incompletely specified Boolean function is transformed into zero polarity incompletely specified MPRM (ISMPRM) by using a novel ISMPRM acquisition algorithm. Secondly, the polarity and allocation of don't care terms of ISMPRM is encoded as chromosome. Lastly, the Pareto optimal solutions are obtained by using NSGA-II, in which MPRM corresponding to the given chromosome is obtained by using a chromosome conversion algorithm. The results on incompletely specified Boolean functions and MCNC benchmark circuits show that a significant power and area improvement can be made compared with the existing power and area optimization approaches of RM circuits.
资助项目	National Natural Science Foundation of China[60973106] ; National Natural Science Foundation of China[61370059] ; National Natural Science Foundation of China[61232009] ; National Natural Science Foundation of China[81571142] ; Beijing Natural Science Foundation[4152030] ; Fundamental Research Funds for the Central Universities of China[YWF-15-GJSYS-085] ; Fundamental Research Funds for the Central Universities of China[YWF-14-JSJXY-14] ; Fund of the State Key Laboratory of Computer Architecture of China[CARCH201507] ; Open Project Program of National Engineering Research Center for Science and Technology Resources Sharing Service (Beihang University) ; Fund of the State Key Laboratory of Software Development Environment of China[SKLSDE-2016ZX-15]
WOS研究方向	Computer Science
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000397835500009
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/7340]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xiao, Li -Min
作者单位	1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Beihang Univ, State Key Lab Software Dev Environm, Beijing 100191, Peoples R China 3.Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China 4.Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 6.Beihang Univ, Natl Engn Res Ctr Sci & Technol Resources Sharing, Beijing 100191, Peoples R China
推荐引用方式 GB/T 7714	He, Zhen-Xue,Xiao, Li -Min,Ruan, Li,et al. A Power and Area Optimization Approach of Mixed Polarity Reed-Muller Expression for Incompletely Specified Boolean Functions[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2017,32(2):297-311.
APA	He, Zhen-Xue.,Xiao, Li -Min.,Ruan, Li.,Gu, Fei.,Huo, Zhi-Sheng.,...&Wang, Xiang.(2017).A Power and Area Optimization Approach of Mixed Polarity Reed-Muller Expression for Incompletely Specified Boolean Functions.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,32(2),297-311.
MLA	He, Zhen-Xue,et al."A Power and Area Optimization Approach of Mixed Polarity Reed-Muller Expression for Incompletely Specified Boolean Functions".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 32.2(2017):297-311.