Title :
Statistical power analysis for nanoscale CMOS
Author :
Wang, Yangang ; Merrett, Michael ; Zwolinski, Mark
Author_Institution :
Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK
Abstract :
With the scaling down of CMOS technology, process variations are becoming significant. Power consumption is a major constraint on IC yield. However, there has been little research on statistical power analysis compared with that on timing analysis. Here, both the static and dynamic power are considered. We characterize a cell library containing mean power. A standard deviation power library is extracted from Monte Carlo simulations. Then, the mean and variance of the power are derived. The proposed technique is validated on benchmark circuits at 35 nm. We compare the results with SPICE simulations and show that the difference is acceptable.
Keywords :
CMOS integrated circuits; Monte Carlo methods; nanoelectronics; power integrated circuits; statistical analysis; Monte Carlo simulation; cell library; dynamic power; mean power; nanoscale CMOS; power consumption; size 35 nm; static power; statistical power analysis; Analytical models; CMOS integrated circuits; Integrated circuit modeling; Inverters; Libraries; Logic gates; Semiconductor device modeling;
Conference_Titel :
Signals and Electronic Systems (ICSES), 2010 International Conference on
Conference_Location :
Gliwice
Print_ISBN :
978-1-4244-5307-8
Electronic_ISBN :
978-83-9047-4-2