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 :
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