OPC optimization and hotspot detection using pattern diffing

Tsung-Wei Lin; Chun Yen Liu; Hung-Yu Lin; Mang-Shiun Chiang; Jason Sweis; Philippe Hurat; Chun Yen Liao; Chun-Sheng Wu; Chao-Yi Huang; Ya-Chieh Lai

doi:10.1117/12.2612476

26 May 2022 OPC optimization and hotspot detection using pattern diffing

Tsung-Wei Lin, Chun Yen Liu, Hung-Yu Lin, Mang-Shiun Chiang, Jason Sweis, Philippe Hurat, Chun Yen Liao, Chun-Sheng Wu, Chao-Yi Huang, Ya-Chieh Lai

Author Affiliations +

Proceedings Volume 12052, DTCO and Computational Patterning; 120521E (2022) https://doi.org/10.1117/12.2612476
Event: SPIE Advanced Lithography + Patterning, 2022, San Jose, California, United States

Conference Poster

Abstract

Beyond the 40nm technology node, layout weak points and hotspot types increase dramatically. Many hotspots can be detected by OPC simulation. However, in advanced nodes, OPC simulation suffers from a long turn-around-time (TAT) and is challenged to handle the additional design complexity. Therefore, in order to speed up the process and OPC development, an efficient OPC hotspot detection method is required. This paper presents a flow using Pegasus Computational Pattern Analytics (CPA) technology from Cadence to extract a comprehensive set of patterns to build a pattern bank from a layout source. We can then compare two or more different banks (diffing) to find new patterns which have not been processed before. OPC engineers can analyze these new patterns to check for any OPC issues instead of simulating a full chip. This flow provides a much higher efficiency and better performance while allowing the storage of pattern banks over time to build history and yield experience. Over time, each new layout introduced for OPC can be processed faster because more patterns have been added to the banks and less simulation time is needed.

Citation Download Citation

Tsung-Wei Lin, Chun Yen Liu, Hung-Yu Lin, Mang-Shiun Chiang, Jason Sweis, Philippe Hurat, Chun Yen Liao, Chun-Sheng Wu, Chao-Yi Huang, and Ya-Chieh Lai "OPC optimization and hotspot detection using pattern diffing", Proc. SPIE 12052, DTCO and Computational Patterning, 120521E (26 May 2022); https://doi.org/10.1117/12.2612476

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