• DocumentCode
    1423078
  • Title

    Efficient statistical approach to estimate power considering uncertain properties of primary inputs

  • Author

    Chen, Zhanping ; Roy, Kaushik ; Chou, Tan-Li

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    6
  • Issue
    3
  • fYear
    1998
  • Firstpage
    484
  • Lastpage
    492
  • Abstract
    Power dissipation in complementary metal-oxide-semiconductor (CMOS) circuits is heavily dependent on the signal properties of the primary inputs. Due to uncertainties in specification of such properties, the average power should be specified between a maximum and a minimum possible value. Due to the complex nature of the problem, it is practically impossible to use traditional power estimation techniques to determine such bounds. In this paper, we present a novel approach to accurately estimate the maximum and minimum bounds for average power using a technique which calculates the sensitivities of average power dissipation to uncertainties in specification of primary inputs. The sensitivities are calculated using a novel statistical technique and can be obtained as a by-product of average power estimation using Monte Carlo-based approaches. The signal properties are specified in terms of signal probability (probability of a signal being logic ONE) and signal activity (probability of signal switching). Results show that the maximum and minimum average power dissipation can vary widely if the primary input probabilities and activities are not specified accurately.
  • Keywords
    CMOS logic circuits; Monte Carlo methods; VLSI; digital simulation; logic CAD; statistical analysis; CMOS; Monte Carlo-based approaches; average power; power estimation; primary inputs; signal probability; signal properties; statistical approach; uncertain properties; CMOS logic circuits; Central Processing Unit; Circuit simulation; Computational modeling; Energy consumption; Power dissipation; Probability; Signal processing; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/92.711319
  • Filename
    711319