DocumentCode :
2791466
Title :
Statistical modeling and post manufacturing configuration for scaled analog CMOS
Author :
Keskin, Gokce ; Proesel, Jonathan ; Pileggi, Larry
Author_Institution :
Dept. of ECE, Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2010
fDate :
19-22 Sept. 2010
Firstpage :
1
Lastpage :
4
Abstract :
Process variations in advanced CMOS process nodes limit the benefits of scaling for analog designs. In the presence of increasing random intra-die variations, mismatch becomes a significant design challenge in circuits such as comparators. In this paper we describe and demonstrate the details of a statistical element selection (SES) methodology that relies on choosing a subset of selectable circuit elements (e.g., input transistors in a comparator) to achieve the desired specification (e.g., offset). Silicon results from a 65nm test chip demonstrate that SES can achieve an order of magnitude better matching than both redundancy and Pelgrom-model sizing given the same core circuit area.
Keywords :
CMOS integrated circuits; comparators (circuits); integrated circuit design; redundancy; CMOS process nodes; Pelgrom-model sizing; SES methodology; analog CMOS; analog designs; comparators; core circuit area; post manufacturing configuration; random intra-die variations; redundancy; selectable circuit elements; statistical element selection methodology; statistical modeling; CMOS integrated circuits; Differential amplifiers; MATLAB; Probability; Redundancy; Semiconductor device modeling; Transistors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Custom Integrated Circuits Conference (CICC), 2010 IEEE
Conference_Location :
San Jose, CA
ISSN :
0886-5930
Print_ISBN :
978-1-4244-5758-8
Type :
conf
DOI :
10.1109/CICC.2010.5617625
Filename :
5617625
Link To Document :
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