DocumentCode
653352
Title
Probabilistic Modeling during Power Estimation for Mixed Polarity Reed-Muller Logic Circuits
Author
Xiang Wang ; Ying Lu ; Yi Zhang ; Zexi Zhao ; Tongsheng Xia ; Jishun Cui ; Limin Xiao
Author_Institution
Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
fYear
2013
fDate
20-23 Aug. 2013
Firstpage
1414
Lastpage
1418
Abstract
Expressing logic functions in terms of Reed-Muller expansions is preferred in some communication circuits for its certain advantages like lower power dissipation. This paper presents a power estimation model for Mixed Polarity Reed-Muller (MPRM) logic circuits from a probabilistic point of view. It is mainly used in combinational circuits under the zero-delay hypothesis. A key feature of this technique is that it provides an accurate and efficient way to handle temporal signal correlations during estimation of average power by using lag-one Markov chains. Besides, an ordered binary-decision diagram (OBDD) based procedure is used to propagate the temporal correlations from the primary inputs throughout the network. This model has been evaluated in the C language and a comparative analysis has been presented for many benchmark circuits. The results show that this model gives very good accuracy and does well in low power design for MPRM logic circuits.
Keywords
Markov processes; Reed-Muller codes; binary decision diagrams; integrated logic circuits; low-power electronics; mixed analogue-digital integrated circuits; C language; benchmark circuits; lag-one Markov chains; mixed polarity Reed-Muller logic circuits; ordered binary-decision diagram; power estimation model; probabilistic modeling; switching activity analysis; temporal correlations; zero-delay hypothesis; Computational modeling; Estimation; Integrated circuit modeling; Logic circuits; Logic gates; Power dissipation; Switches; Markov chains; Probabilistic power estimation; Reed-Muller logic; Switching activity analysis; Temporal correlations;
fLanguage
English
Publisher
ieee
Conference_Titel
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location
Beijing
Type
conf
DOI
10.1109/GreenCom-iThings-CPSCom.2013.247
Filename
6682259
Link To Document