Multi-wafer virtual probe: Minimum-cost variation characterization by exploring wafer-to-wafer correlation

Published

Conference Paper

In this paper, we propose a new technique, referred to as MultiWafer Virtual Probe (MVP) to efficiently model wafer-level spatial variations for nanoscale integrated circuits. Towards this goal, a novel Bayesian inference is derived to extract a shared model template to explore the wafer-to-wafer correlation information within the same lot. In addition, a robust regression algorithm is proposed to automatically detect and remove outliers (i.e., abnormal measurement data with large error) so that they do not bias the modeling results. The proposed MVP method is extensively tested for silicon measurement data collected from 200 wafers at an advanced technology node. Our experimental results demonstrate that MVP offers superior accuracy over other traditional approaches such as VP [7] and EM [8], if a limited number of measurement data are available. ©2010 IEEE.

Full Text

Duke Authors

Cited Authors

  • Zhang, W; Li, X; Acar, E; Liu, F; Rutenbar, R

Published Date

  • December 1, 2010

Published In

Start / End Page

  • 47 - 54

International Standard Serial Number (ISSN)

  • 1092-3152

International Standard Book Number 13 (ISBN-13)

  • 9781424481927

Digital Object Identifier (DOI)

  • 10.1109/ICCAD.2010.5654349

Citation Source

  • Scopus