DocumentCode
1504168
Title
Efficient Additive Statistical Leakage Estimation
Author
Cheng, Lerong ; Gupta, Puneet ; He, Lei
Author_Institution
Univ. of California at Los Angeles, Los Angeles, CA, USA
Volume
28
Issue
11
fYear
2009
Firstpage
1777
Lastpage
1781
Abstract
Nominal power estimation is quick but gives minimal information. Statistical power analysis can provide information on yield, chip robustness, etc., but current methods are unnecessarily slow and complex. This is primarily because existing leakage-power models, which model leakage power as lognormal distribution and calculate chip leakage power based on Wilkinson´s approach, are not directly additive. Hence, for each incremental change of the circuit, the covariances between each pair of circuit elements need to be recalculated, which is inefficient. In this paper, we proposed a simple additive polynomial leakage-variation model. With additivity, we can calculate chip leakage power and leakage power after incremental change very efficiently. Experimental results show that our method is five times faster than the existing Wilkinson´s approach while having no accuracy loss in mean estimation and about 1% accuracy loss in standard-deviation and 99%-percentile-point estimations.
Keywords
application specific integrated circuits; field programmable gate arrays; integrated circuit modelling; log normal distribution; polynomial approximation; ASIC; Wilkinson approach; additive polynomial leakage-variation model; additive statistical leakage estimation; application specific integrated circuit; field programmable gate array circuit; leakage power model; lognormal distribution; polynomial approximation; statistical power analysis; Circuits; Delay; Energy consumption; Helium; Information analysis; Polynomials; Profitability; Robustness; Virtual manufacturing; Yield estimation; Leakage power; process variation; yield modeling;
fLanguage
English
Journal_Title
Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0278-0070
Type
jour
DOI
10.1109/TCAD.2009.2030433
Filename
5290345
Link To Document