Publications

Summary: IEEE TCAD (26), DAC (20), ICCAD (16), etc.

Journal & Conference Papers

Selected Preprints

  • Kang Liu, Haoyu Yang, Yuzhe Ma, Benjamin Tan, Bei Yu, Evangeline F. Y. Young, Ramesh Karri, Siddharth Garg, “Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection”. (arXiv)

  • Haoyu Yang, Shuhe Li, Cyrus Tabery, Bingqing Lin, Bei Yu, “Bridging the Gap Between Layout Pattern Sampling and Hotspot Detection via Batch Active Learning”. (arXiv)

Accepted

2020


  • [C98] Wei Li, Jialu Xia, Yuzhe Ma, Jialu Li, Yibo Lin, Bei Yu, “Adaptive Layout Decomposition with Graph Embedding Neural Networks”, ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, July 19–23, 2020.

  • [C97] Wei Zhong, Shuxiang Hu, Yuzhe Ma, Haoyu Yang, Xiuyuan Ma, Bei Yu, “Deep Learning-Driven Simultaneous Layout Decomposition and Mask Optimization”, ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, July 19–23, 2020.

  • [C96] Husheng Zhou, Wei Li, Zelun Kong, Junfeng Guo, Yuqun Zhang, Bei Yu, Lingming Zhang, Cong Liu, “DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems”, ACM/IEEE International Conference on Software Engineering (ICSE), Seoul, May 23–29, 2020. (arXiv)

  • [C95] Junpeng Wang, Qi Xu, Bo Yuan, Song Chen, Bei Yu, Feng Wu, “Reliability-Driven Neural Network Training for Memristive Crossbar-Based Neuromorphic Computing Systems”, IEEE International Symposium on Circuits and Systems (ISCAS), Sevilla, Spain, May 17–20, 2020.

  • [C93] Haoyu Yang, Wei Zhong, Yuzhe Ma, Hao Geng, Ran Chen, Wanli Chen, Bei Yu, “VLSI Mask Optimization: From Shallow To Deep Learning”, IEEE/ACM Asian and South Pacific Design Automation Conference (ASPDAC), Beijing, Jan. 13–16, 2020. (arXiv) (slides) (Invited Paper)

2019


  • [C89] Yuzhe Ma, Ziyang Yu, Bei Yu, “CAD Tool Design Space Exploration via Bayesian Optimization”, ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), Alberta, Canada, Sep. 3–4, 2019. (arXiv)

  • [C88] Haoyu Yang, Wen Chen, Piyush Pathak, Frank Gennari, Ya-Chieh Lai, Bei Yu, “Automatic Layout Generation with Applications in Machine Learning Engine Evaluation”, ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), Alberta, Canada, Sep. 3–4, 2019. (arXiv)

  • [C87] Zhonghua Zhou, Ziran Zhu, Jianli Chen, Yuzhe Ma, Bei Yu, Tsung-Yi Ho, Guy Lemieux, Andre Ivano, “Congestion-aware Global Routing using Deep Convolutional Generative Adversarial Networks”, ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), Alberta, Canada, Sep. 3–4, 2019.

  • [C80] Bentian Jiang, Xiaopeng Zhang, Ran Chen, Gengjie Chen, Peishan Tu, Wei Li, Evangeline F. Y. Young, Bei Yu, “FIT: Fill Insertion Considering Timing”, ACM/IEEE Design Automation Conference (DAC), pp. 221:1–221:6, Las Vegas, NV, June 2–6, 2019. (paper) (slides) (poster)

2018


2017


  • [C57] Hang Zhang, Fengyuan Zhu, Haocheng Li, Evangeline F. Y. Young, Bei Yu, “Bilinear Lithography Hotspot Detection”, ACM International Symposium on Physical Design (ISPD), pp. 7–14, Portland, OR, Mar. 19–22, 2017. (paper) (Best Paper Award)

2016


2015


2014

2013


2012


  • [C13] Bei Yu, Jhih-Rong Gao, Duo Ding, Yongchan Ban, Jae-Seok Yang, Kun Yuan, Minsik Cho, David Z. Pan, “Dealing with IC Manufacturability in Extreme Scaling”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), pp. 240–242, San Jose, CA, Nov. 5–8, 2012. (paper) (Embedded Tutorial paper)

2011

2010

2009



Books / Book Chapters

 

[B2] Bei Yu, David Z. Pan, “Design for Manufacturability with Advanced Lithography”, Springer, 2016.

 

[B1] Bei Yu, David Z. Pan, “Layout Decomposition for Triple Patterning”, in Encyclopedia of Algorithms, M.-Y. Kao eds., Springer, 2015. (paper)


Dissertation

Newsletters

  • [N2] Bei Yu, Gilda Garreton, David Z. Pan, “Layout Compliance for Triple Patterning Lithography: An Iterative Approach”, SPIE Newsroom.