• 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