DeePattern: Layout Pattern Generation with Transforming Convolutional Auto-Encoder Haoyu Yang 1 , Piyush Pathak 2 , Frank Gennari 2 , Ya-Chieh Lai 2 , Bei Yu 1 1 The Chinese University of Hong Kong 2 Cadence Design Systems, Inc. 1 / 16
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Related Works (a) (b) (c) ◮ Transferring from previous technology node (not applicable for large technology node gap † ) ◮ Randomly placing patterns according to certain constraints (limited diversity) ◮ Generative machine learning models (violating design rules) † Linda Zhuang et al. (2016). “A novel methodology of process weak-point identification to accelerate process development and yield ramp-up”. In: Proc. ICSICT , pp. 852–855. 3 / 16
Pattern Generation Challenges Satisfying design rules Pitch T2T Width Length Coverage of the design space ◮ The complexity of a pattern in x and y directions (denoted as c x and c y ) are defined as the number of scan lines subtracted by one along x -axis and y -axis, respectively. ◮ The diversity of a pattern library is given by the Shannon Entropy of the pattern complexity sampled from the library, � � H = − P ( c xi , c yj ) log P ( c xi , c yj ) , i j where P ( c xi , c yj ) is the probability of a pattern sampled from the library has complexities of c xi and c yj in x and y directions respectively. 4 / 16
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