Handling partial correlations in yield prediction

Sridhar Varadan, Janet Wang, Jiang Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In nanometer regime, IC designs have to consider the impact of process variations, which is often indicated by manufacturing/parametric yield. This paper investigates a yield model - the probability that the values of multiple manufacturing/circuit parameters meet certain target. This model can be applied to predict CMP (Chemical-Mechanical Planarization) yield. We focus on the difficult cases which have large number of partially correlated variations. In order to predict the yield for these difficult cases efficiently, we propose two techniques: (1) application of Orthogonal Principle Component Analysis (OPCA); (2) hierarchical adaptive quadrisection (HAQ). Systematic variations are also included in our model. Compared to previous work, the OPCA based method can reduce the error on yield estimation from 17.1%-21.1% to 1.3%-2.8% with 4.6 × speedup. The HAQ technique can reduce the error to 4.1% - 5.6% with 6 × -9.4 × speedup.

Original languageEnglish (US)
Title of host publication2008 Asia and South Pacific Design Automation Conference, ASP-DAC
Pages543-548
Number of pages6
DOIs
StatePublished - Aug 21 2008
Event2008 Asia and South Pacific Design Automation Conference, ASP-DAC - Seoul, Korea, Republic of
Duration: Mar 21 2008Mar 24 2008

Publication series

NameProceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Other

Other2008 Asia and South Pacific Design Automation Conference, ASP-DAC
CountryKorea, Republic of
CitySeoul
Period3/21/083/24/08

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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  • Cite this

    Varadan, S., Wang, J., & Hu, J. (2008). Handling partial correlations in yield prediction. In 2008 Asia and South Pacific Design Automation Conference, ASP-DAC (pp. 543-548). [4484010] (Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC). https://doi.org/10.1109/ASPDAC.2008.4484010