Dynamic pattern match searching flow to enable precise hotspot detection

Fadi Batarseh; Uwe Paul Schroeder; Jeff Nelson; Piyush Pathak; Wei-Long Wang; Ya-Chieh Lai

doi:10.1117/12.2617261

26 May 2022 Dynamic pattern match searching flow to enable precise hotspot detection

Fadi Batarseh, Uwe Paul Schroeder, Jeff Nelson, Piyush Pathak, Wei-Long Wang, Ya-Chieh Lai

Proceedings Volume 12052, DTCO and Computational Patterning; 120520O (2022) https://doi.org/10.1117/12.2617261
Event: SPIE Advanced Lithography + Patterning, 2022, San Jose, California, United States

Abstract

This paper demonstrates a new approach for hotspot detection in large design spaces. We present a new pattern matching technique, which is a multi-window pattern search that is deployed in a dynamic and precise way to search for similar patterns. Based on the matched locations the flow extracts and combines silicon awareness features and design level features to build comprehensive feature matrix that can be used in subsequent analytical analysis. The paper also shows the advantage of using this flow with respect to precise capture of hotspot and ~10X improvement on turnaround time for feature extraction compared with traditional methods. The output of this flow also facilitates and improves the data preparation process for machine learning model building.

Conference Presentation

Citation Download Citation

Fadi Batarseh, Uwe Paul Schroeder, Jeff Nelson, Piyush Pathak, Wei-Long Wang, and Ya-Chieh Lai "Dynamic pattern match searching flow to enable precise hotspot detection", Proc. SPIE 12052, DTCO and Computational Patterning, 120520O (26 May 2022); https://doi.org/10.1117/12.2617261

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