Indirect performance sensing for on-chip analog self-healing via Bayesian model fusion

Published

Conference Paper

On-chip analog self-healing requires low-cost sensors to accurately measure various performance metrics. In this paper we propose a novel approach of indirect performance sensing based upon Bayesian model fusion (BMF) to facilitate inexpensive-yet-accurate on-chip performance measurement. A 25GHz differential Colpitts voltage-controlled oscillator (VCO) designed in a 32nm CMOS SOI process is used to validate the proposed indirect performance sensing and self-healing methodology. Our silicon measurement results demonstrate that the parametric yield of the VCO is improved from 0% to 69.17% for a wafer after the proposed self-healing is applied. © 2013 IEEE.

Full Text

Duke Authors

Cited Authors

  • Sun, S; Wang, F; Yaldiz, S; Li, X; Pileggi, L; Natarajan, A; Ferriss, M; Plouchart, J; Sadhu, B; Parker, B; Valdes-Garcia, A; Sanduleanu, M; Tierno, J; Friedman, D

Published Date

  • November 7, 2013

Published In

International Standard Serial Number (ISSN)

  • 0886-5930

International Standard Book Number 13 (ISBN-13)

  • 9781467361460

Digital Object Identifier (DOI)

  • 10.1109/CICC.2013.6658489

Citation Source

  • Scopus