Spatial variation decomposition via sparse regression

Wangyang Zhang; Karthik Balakrishnan; Xin Li; Duane Boning; Emrah Acar; Frank Liu; Robin A Rutenbar

doi:10.1109/ICICDT.2012.6232875

Spatial variation decomposition via sparse regression

Wangyang Zhang, Karthik Balakrishnan, Xin Li, Duane Boning, Emrah Acar, Frank Liu, Robin A Rutenbar

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we briefly discuss the recent development of a novel sparse regression technique that aims to accurately decompose process variation into two different components: (1) spatially correlated variation, and (2) uncorrelated random variation. Such variation decomposition is important to identify systematic variation patterns at wafer and/or chip level for process modeling, control and diagnosis. We demonstrate that the spatially correlated variation can be accurately represented by the linear combination of a small number of "templates". Based upon this observation, an efficient algorithm is developed to accurately separate spatially correlated variation from uncorrelated random variation. Several examples based on silicon measurement data demonstrate that the aforementioned sparse regression technique can capture systematic variation patterns with high accuracy.

Original language	English (US)
Title of host publication	ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology
DOIs	https://doi.org/10.1109/ICICDT.2012.6232875
State	Published - Aug 13 2012
Event	IEEE International Conference on Integrated Circuit Design and Technology, ICICDT 2012 - Austin, TX, United States Duration: May 30 2012 → Jun 1 2012

Publication series

Name	ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology

Other

Other	IEEE International Conference on Integrated Circuit Design and Technology, ICICDT 2012
Country	United States
City	Austin, TX
Period	5/30/12 → 6/1/12

Keywords

integrated circuit
process variation
variation decomposition

ASJC Scopus subject areas

Hardware and Architecture
Electrical and Electronic Engineering

Access to Document

10.1109/ICICDT.2012.6232875

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Cite this

Zhang, W., Balakrishnan, K., Li, X., Boning, D., Acar, E., Liu, F., & Rutenbar, R. A. (2012). Spatial variation decomposition via sparse regression. In ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology [6232875] (ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology). https://doi.org/10.1109/ICICDT.2012.6232875

Spatial variation decomposition via sparse regression. / Zhang, Wangyang; Balakrishnan, Karthik; Li, Xin; Boning, Duane; Acar, Emrah; Liu, Frank; Rutenbar, Robin A.

ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology. 2012. 6232875 (ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, W, Balakrishnan, K, Li, X, Boning, D, Acar, E, Liu, F & Rutenbar, RA 2012, Spatial variation decomposition via sparse regression. in ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology., 6232875, ICICDT 2012 - IEEE International Conference on Integrated Circuit Design and Technology, IEEE International Conference on Integrated Circuit Design and Technology, ICICDT 2012, Austin, TX, United States, 5/30/12. https://doi.org/10.1109/ICICDT.2012.6232875

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