Partial least squares-preconditioned importance sampling for fast circuit yield estimation

Yu Ben; Costas J. Spanos

doi:10.1117/12.878725

4 April 2011 Partial least squares-preconditioned importance sampling for fast circuit yield estimation

Yu Ben, Costas J. Spanos

Proceedings Volume 7974, Design for Manufacturability through Design-Process Integration V; 79740P (2011) https://doi.org/10.1117/12.878725
Event: SPIE Advanced Lithography, 2011, San Jose, California, United States

Abstract

We propose a partial least squares (PLS)-preconditioned importance sampling method for yield estimation. The method makes use of the rotating vector obtained through PLS regression, and finds the boundary point along the vector by line search. A biased distribution is constructed around that point for subsequent importance sampling simulation. This method is shown to be much more stable and efficient than existing approaches and is validated via an SRAM example.

Citation Download Citation

Yu Ben and Costas J. Spanos "Partial least squares-preconditioned importance sampling for fast circuit yield estimation", Proc. SPIE 7974, Design for Manufacturability through Design-Process Integration V, 79740P (4 April 2011); https://doi.org/10.1117/12.878725

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available