NDLI: Statistical Analysis Model of Nano-CMOS Variability with Intra-die Correlation Due to Proximity

Content Provider	IEEE Xplore Digital Library
Author	Zheng Xie Edwards, D.
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Sci., Univ. of Manchester, Manchester, UK (Edwards, D.) \|\| Sch. of Comput., Math. & Digital Technol., Manchester Metropolitan Univ., Manchester, UK (Zheng Xie)
Abstract	The intrinsic variability of nano-scale integrated circuit (IC) technology must be taken into account when analyzing circuit designs to predict likely yield. Monte Carlo (MC) and quasi-MC (QMC) based statistical techniques aim to do this by analysing many randomized copies of the circuit. The randomization must model many forms of variability that are to be expected in nano-CMOS technology which include 'atomistic' effects without intra-die correlation and also effects with intra-die correlation due to the proximity of neighbouring devices. The means of randomizing parameters with intra-die correlation as predicted by an 'exponential' model of proximity effects, is demonstrated. Examples are presented to show that the effects of intra-die correlation on statistical performance distribution and failure yield prediction can be significant, and that ignoring this correlation can give pessimistic estimates of yield.
Starting Page	628
Ending Page	632
File Size	184539
Page Count	5
File Format	PDF
ISBN	9780769550732
DOI	10.1109/EUROSIM.2013.109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-10
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nano-scale integrated circuit Statistical performance distribution Proximity Yield failure prediction Quasi-Monte Carlo (QMC) Monte Carlo (MC) statistical techniques Intra-die correlation Nano-CMOS variability
Content Type	Text
Resource Type	Article

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