Details

Autor(en) / Beteiligte

• Xiao, Zigang
• Du, Yuelin
• Tian, Haitong
• Wong, Martin
• Yi, He
• Wong, H.-S
• Zhang, Hongbo

Titel

Directed Self-Assembly (DSA) Template Pattern Verification

Ist Teil von

• 2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC), 2014, p.1-6

Ort / Verlag

ACM

Erscheinungsjahr

2014

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Xplore

Beschreibungen/Notizen

• Directed Self-Assembly (DSA) is a promising technique for contacts/vias patterning, where groups of contacts/vias are patterned by guiding templates. As the templates are patterned by traditional lithography, their shapes may vary due to the process variations, which will ultimately affect the contacts/vias even for the same type of template. Due to the complexity of the DSA process, rigorous process simulation is unacceptably slow for full chip verification. This paper formulate several critical problems in DSA verification, and proposes a design automation methodology that consists of a data preparation and a model learning stage. We present a novel DSA model with Point Correspondence and Segment Distance features for robust learning. Following the methodology, we propose an effective machine learning (ML) based method for DSA hotspot detection. The results of our initial experiments have already demonstrated the high-efficiency of our ML-based approach with over 85% detection accuracy. Compared to the minutes or even hours of simulation time in rigorous method, the methodology in this paper validates the research potential along this direction.