NDLI: Advances in variation-aware modeling, verification, and testing of analog ICs

Content Provider	IEEE Xplore Digital Library
Author	De Jonghe, D. Maricau, E. Gielen, G. McConaghy, T. Tasic, B. Stratigopoulos, H.
Copyright Year	2012
Description	Author affiliation: TIMA Laboratory, Grenoble, France (Stratigopoulos, H.) \|\| Solido Design Automation Inc., Canada (McConaghy, T.) \|\| NXP Semiconductor Inc., Eindhoven, The Netherlands (Tasic, B.) \|\| K.U. Leuven, Heverlee, Belgium (De Jonghe, D.; Maricau, E.; Gielen, G.)
Abstract	This tutorial paper describes novel scalable, nonlinear/generic, and industrially-oriented approaches to perform variation-aware modeling, verification, fault simulation, and testing of analog/custom ICs. In the first section, Dimitri De Jonghe, Elie Maricau, and Georges Gielen present a new advance in extracting highly nonlinear, variation-aware behavioral models, through the use of data mining and a re-framing of the model-order reduction problem. In the next section, Trent McConaghy describes new statistical machine learning techniques that enable new classes of industrial EDA tools, which in turn are enabling designers to perform fast and accurate PVT / statistical / high-sigma design and verification. In the third section, Bratislav Tasić presents a novel industrially-oriented approach to analog fault simulation that also has applicability to variation-aware design. In the final section, Haralampos Stratigopoulos describes describes state-of-the-art analog testing approaches that address process variability.
Starting Page	1615
Ending Page	1620
File Size	726513
Page Count	6
File Format	PDF
ISBN	9781457721458
ISSN	15301591
DOI	10.1109/DATE.2012.6176730
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-12
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	European Design Automation Association (EDAA)
Subject Keyword	Circuit faults Integrated circuit modeling Performance evaluation Sensors Thin film transistors Algorithm design and analysis Monte Carlo methods
Content Type	Text
Resource Type	Article

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