DocumentCode
3193801
Title
A Design Model for Random Process Variability
Author
Wang, Victoria ; Agarwal, Kanak ; Nassif, Sani ; Nowka, Kevin ; Markovic, Dejan
Author_Institution
Univ. of California, Los Angeles
fYear
2008
fDate
17-19 March 2008
Firstpage
734
Lastpage
737
Abstract
A new approach to analyze process variation through measured current variation is introduced. The methodology concludes with a simple and convenient posynomial model for random process variability to bridge the gap between existing statistical methods and circuit design. The model contains only design variables: transistor sizes W and L, and operating points Vgs and Vds. Modeling random process variability in this way allows for adaptability to optimization problems, time efficient methods for gathering statistical information in comparison to Monte Carlo, and an alternative equation for hand analysis.
Keywords
integrated circuit design; integrated circuit modelling; random processes; statistical analysis; Monte Carlo method; current variation; integrated circuit design; posynomial model; random process variability; statistical information; statistical methods; Bridge circuits; Circuit synthesis; Current distribution; Current measurement; Equations; Gaussian distribution; MOSFETs; Metrology; Random processes; Testing; current variation; modeling; principal component analysis; random process variability;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality Electronic Design, 2008. ISQED 2008. 9th International Symposium on
Conference_Location
San Jose, CA
Print_ISBN
978-0-7695-3117-5
Type
conf
DOI
10.1109/ISQED.2008.4479829
Filename
4479829
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