Virtual probe: A statistical framework for low-cost silicon characterization of nanoscale integrated circuits

Published

Journal Article

In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize, and monitor spatially-correlated inter-die and/or intra-die variations in nanoscale manufacturing process. VP exploits recent breakthroughs in compressed sensing to accurately predict spatial variations from an exceptionally small set of measurement data, thereby reducing the cost of silicon characterization. By exploring the underlying sparse pattern in spatial frequency domain, VP achieves substantially lower sampling frequency than the well-known Nyquist rate. In addition, VP is formulated as a linear programming problem and, therefore, can be solved both robustly and efficiently. Our industrial measurement data demonstrate the superior accuracy of VP over several traditional methods, including 2-D interpolation, Kriging prediction, and k-LSE estimation. © 2006 IEEE.

Full Text

Duke Authors

Cited Authors

  • Zhang, W; Li, X; Liu, F; Acar, E; Rutenbar, RA; Blanton, RD

Published Date

  • December 1, 2011

Published In

Volume / Issue

  • 30 / 12

Start / End Page

  • 1814 - 1827

International Standard Serial Number (ISSN)

  • 0278-0070

Digital Object Identifier (DOI)

  • 10.1109/TCAD.2011.2164536

Citation Source

  • Scopus