{"title":"Nonparametric estimation of average power dissipation in CMOS VLSI circuits","authors":"L. Yuan, Chin-Chi Teng, S. Kang","doi":"10.1109/CICC.1996.510548","DOIUrl":null,"url":null,"abstract":"In this paper, we present a new statistical technique for estimation of average power dissipation in digital circuits. Present statistical techniques estimate the average power based on the assumption that the power distribution can be characterized by a preassumed function. Large errors can occur when the assumption is not met. To overcome this problem, we propose a nonparametric technique in which no distribution function needs to be assumed. A distribution-independent upper and lower bound of the average power are derived from the Kolmogorov-Smirnov theorem. A stopping criterion is designed based on the bounds for a desired percentage error with a specified confidence level. Since it does not resort to the assumption of any particular distribution function, the technique can be applied to all the circuits irrespective of their power distributions.","PeriodicalId":74515,"journal":{"name":"Proceedings of the ... Custom Integrated Circuits Conference. Custom Integrated Circuits Conference","volume":"40 1","pages":"225-228"},"PeriodicalIF":0.0000,"publicationDate":"1996-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... Custom Integrated Circuits Conference. Custom Integrated Circuits Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICC.1996.510548","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we present a new statistical technique for estimation of average power dissipation in digital circuits. Present statistical techniques estimate the average power based on the assumption that the power distribution can be characterized by a preassumed function. Large errors can occur when the assumption is not met. To overcome this problem, we propose a nonparametric technique in which no distribution function needs to be assumed. A distribution-independent upper and lower bound of the average power are derived from the Kolmogorov-Smirnov theorem. A stopping criterion is designed based on the bounds for a desired percentage error with a specified confidence level. Since it does not resort to the assumption of any particular distribution function, the technique can be applied to all the circuits irrespective of their power distributions.