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Proceedings Paper

An efficient way of automatic layout decomposition and pattern classification
Author(s): Zhenzhen Wan; Limei Liu; Huan Kan; Qijian Wan; Xinyi Hu; Zhengfang Liu; Chunshan Du
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Paper Abstract

As technology advances, chip size becomes larger and larger, this brings challenges when engineers would like to do a quick investigation of the design in a short time, like hotspot detection and layout fixing. An idea to mitigate the challenges is to decompose a layout into patterns and classify these patterns to unique ones. Engineers then prioritize their work on these unique patterns. Patterns from different products can be accumulated and recorded, when a new design comes in, the known patterns will be filtered out from all unique patterns seen in this new design. When the pattern database is large enough and contains enough safe and weak patterns, machine learning can be used to train the algorithm to predict hotspots in the new design. The key point is how to efficiently decompose a layout and group those patterns. This paper presents how to decompose a layout by using Calibre Pattern Matching and DRC. The experiment data shows that this is a very efficient way to decompose a layout automatically.

Paper Details

Date Published: 20 March 2019
PDF: 6 pages
Proc. SPIE 10962, Design-Process-Technology Co-optimization for Manufacturability XIII, 1096214 (20 March 2019); doi: 10.1117/12.2515137
Show Author Affiliations
Zhenzhen Wan, SMIC (China)
Limei Liu, SMIC (China)
Huan Kan, SMIC (China)
Qijian Wan, Mentor Graphics Corp. (China)
Xinyi Hu, Mentor Graphics Corp. (China)
Zhengfang Liu, Mentor Graphics Corp. (China)
Chunshan Du, Mentor Graphics Corp. (China)

Published in SPIE Proceedings Vol. 10962:
Design-Process-Technology Co-optimization for Manufacturability XIII
Jason P. Cain, Editor(s)

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