EasyMRC: Efficient Mask Rule Checking via Representative Edge Sampling

The photolithography process is getting more sophisticated with technology node scaling down and VLSI designs becoming complex. As photomask patterns get finer, mask rule checks (MRCs) are inevitable to avoid discrepancies in the layout and to ensure manufacturability. This paper introduces an efficient mask rule checking approach that utilizes a representative edge sampling scheme. The representative edge sampling scheme selects a subset of edges and points of each polygon that capture its contour, meanwhile greatly reducing the number of edges involved in actual checking. Experimental results demonstrate that the proposed approach achieves significant speedup compared with the state-of-the-art academic tool.

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Publication Details

Journal
ACM Transactions on Design Automation of Electronic Systems
Published
2025-03-17
DOI
https://doi.org/10.1145/3723044
Citations
2
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
2.97
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article

EasyMRC: Efficient Mask Rule Checking via Representative Edge Sampling

Zhuolun He, Bei Yu, Wenjian Yu, Shuo Yin et al.
2 citations
ACM Transactions on Design Automation of Electronic Systems
Data Management and Algorithms
2.97
article

EasyMRC: Efficient Mask Rule Checking via Representative Edge Sampling

Zhuolun He, Bei Yu, Wenjian Yu, Shuo Yin, Yuan Pu, Jiren Xu
article en
2 citations

Abstract

The photolithography process is getting more sophisticated with technology node scaling down and VLSI designs becoming complex. As photomask patterns get finer, mask rule checks (MRCs) are inevitable to avoid discrepancies in the layout and to ensure manufacturability. This paper introduces an efficient mask rule checking approach that utilizes a representative edge sampling scheme. The representative edge sampling scheme selects a subset of edges and points of each polygon that capture its contour, meanwhile greatly reducing the number of edges involved in actual checking. Experimental results demonstrate that the proposed approach achieves significant speedup compared with the state-of-the-art academic tool.

ACM Transactions on Design Automation of Electronic Systems
Chinese University of Hong Kong (HK), Tsinghua University (CN)
Openalex Percentile: Top 11%
Data Management and Algorithms
2.97
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