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

Wangyang Zhang, Xin Li, Frank Liu, Emrah Acar, Rob A. Rutenbar, Ronald D. Blanton

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number6071091
Pages (from-to)1814-1827
Number of pages14
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume30
Issue number12
DOIs
StatePublished - Dec 1 2011

Keywords

  • Characterization
  • compressed sensing
  • integrated circuit
  • process variation

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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