Maximum power estimation using the limiting distributions of extreme order statistics

Qinru Qiu, Qing Wu, Massoud Pedram

Research output: Chapter in Book/Entry/PoemConference contribution

10 Scopus citations


In this paper we present a statistical method for estimating the maximum power consumption in VLSI circuits. The method is based on the theory of extreme order statistics applied to the probabilistic distribution of the cycle-based power consumption, maximum likelihood estimation, and Monte-Carlo simulation. The method can predict the maximum power in the constrained space of given input vector pairs as well as the complete space of all possible input vector pairs. The simulation-based nature of the proposed method allows one to avoid the limitations imposed by simple gate-level delay models and handle arbitrary circuit structures. The proposed method can produce maximum power estimates to satisJL user-specified error and confidence levels. Experimental results show that this method provides maximum power estimates within 5% of the actual value and with a 90% confidence level by simulating, on average, about 2.500 vector pairs.

Original languageEnglish (US)
Title of host publicationProceedings 1998 - Design and Automation Conference, DAC 1998
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)078034409X
StatePublished - 1998
Externally publishedYes
Event35th Design and Automation Conference, DAC 1998 - San Francisco, United States
Duration: Jun 15 1998Jun 19 1998

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Conference35th Design and Automation Conference, DAC 1998
Country/TerritoryUnited States
CitySan Francisco

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation
  • Hardware and Architecture


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