Publications

Summary: IEEE TCAD (54), DAC (36), ICCAD (33), etc.

Journal & Conference Papers

Accepted

2023

  • [C170] Zhuolun He, Yihang Zuo, Jiaxi Jiang, Haisheng Zheng, Yuzhe Ma, Bei Yu, “OpenDRC: An Efficient Open-Source Design Rule Checking Engine with Hierarchical GPU Acceleration”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C169] Peiyu Liao, Hongduo Liu, Yibo Lin, Bei Yu, Martin Wong, “On a Moreau Envelope Wirelength Model for Analytical Global Placement”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C168] Siting Liu, Ziyi Wang, Fangzhou Liu, Yibo Lin, Bei Yu, Martin Wong, “Concurrent Sign-off Timing Optimization via Deep Steiner Points Refinement”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C167] Hongduo Liu, Peiyu Liao, Mengchuan Zou, Bowen Pang, Xijun Li, Mingxuan Yuan, Tsung-Yi Ho, Bei Yu, “Layout Decomposition via Boolean Satisfiability”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C166] Guojin Chen, Zehua Pei, Haoyu Yang, Yuzhe Ma, Bei Yu, Martin Wong, “Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C165] Ziyi Wang, Siting Liu, Yuan Pu, Song Chen, Tsung-Yi Ho, Bei Yu, “Realistic Sign-off Timing Prediction via Multimodal Fusion”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C164] Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu, “DiffPattern: Layout Pattern Generation via Discrete Diffusion”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C163] Su Zheng, Lancheng Zou, Siting Liu, Yibo Lin, Bei Yu, Martin Wong, “Mitigating Distribution Shift for Congestion Optimization in Global Placement”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C162] Yu Zhang, Yifan Chen, Zhonglin Xie, Hong Xu, Zaiwen Wen, Yibo Lin, Bei Yu, “LRSDP: Low-Rank SDP for Triple Patterning Lithography Layout Decomposition”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C161] Shuyuan Sun, Fan Yang, Bei Yu, Li Shang, Xuan Zeng, “Efficient ILT via Multi-level Lithography Simulation”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023.

  • [C160] Guyue Huang, Yang Bai, Liu Liu, Yuke Wang, Bei Yu, Yufei Ding, Yuan Xie, “ALCOP: Automatic Load-Compute Pipelining in Deep Learning Compiler for AI-GPUs”, Conference on Machine Learning and Systems (MLSys), Jun. 04–08, 2023.

  • [C159] Yuyang Ye, Tinghuan Chen, Yifei Gao, Hao Yan, Bei Yu, Longxing Shi, “Fast and Accurate Wire Timing Estimation Based on Graph Learning”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Antwerp, Belgium, Apr. 17–19, 2023. (paper)

  • [C158] Wei Zhong, Zhenhua Feng, Zhuolun He, Weimin Wang, Yuzhe Ma, Bei Yu, “Enabling Efficient Design Rule Checking with GPU Acceleration”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Antwerp, Belgium, Apr. 17–19, 2023. (paper)

  • [C157] Rongliang Fu, Junying Huang, Mengmeng Wang, Yoshikawa Nobuyuki, Bei Yu, Tsung-Yi Ho, Olivia Chen, “BOMIG: A Majority Logic Synthesis Framework for AQFP Logic”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Antwerp, Belgium, Apr. 17–19, 2023. (paper)

  • [C156] Guojin Chen, Haoyu Yang, Bei Yu, “GPU Accelerated Matrix Cover Algorithm for Multiple Patterning Layout Decomposition”, SPIE Intl. Symp. Advanced Lithography Conference, San Jose, Feb. 26–Mar. 02, 2023.

  • [C155] Yuxuan Zhao, Qi Sun, Zhuolun He, Yang Bai, Bei Yu, “AutoGraph: Optimizing DNN Computation Graph for Parallel GPU Kernel Execution”, AAAI Conference on Artificial Intelligence (AAAI), Feb. 7–14, 2023. (paper) (slides) (poster) (video)


2022


  • [J71] Martin Rapp, Hussam Amrouch, Yibo Lin, Bei Yu, David Z. Pan, Marilyn Wolf, Jorg Henkel, “MLCAD: A Survey of Research in Machine Learning for CAD”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 10, pp. 3162–3181, 2022. (paper) (Keynote Paper)

  • [J64] Yibo Lin, Xiaohan Gao, Tinghuan Chen, Bei Yu, “Machine learning for digital circuit backend design”, Micro/nano Electronics and Intelligent Manufacturing, vol. 2, no. 3, 2022. (in Chinese) (paper)

  • [J61] Ran Chen, Wei Zhong, Haoyu Yang, Hao Geng, Fan Yang, Xuan Zeng, Bei Yu, “Faster Region-based Hotspot Detection”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 3, pp. 669–680, 2022. (code) (paper)

2021

  • [C118] Tinghuan Chen, Qi Sun, Bei Yu, “Machine Learning in Nanometer AMS Design for Reliability”, IEEE International Conference on ASIC (ASICON), Kunming, China, Oct. 26–29, 2021. (paper) (slides) (Invited Paper)

  • [C116] Wei Li, Guojin Chen, Haoyu Yang, Ran Chen, Bei Yu, “Learning Point Clouds in EDA”, ACM International Symposium on Physical Design (ISPD), Mar. 21–Mar. 24, 2021. (paper) (slides) (Invited Paper)

  • [C111] Hongjia Li, Mengshu Sun, Tianyun Zhang, Olivia Chen, Nobuyuki Yoshikawa, Bei Yu, Yanzhi Wang, Yibo Lin, “Towards AQFP-Capable Physical Design Automation”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Feb. 01–05, 2021. (paper)


  • [J58] Wei Li, Yuzhe Ma, Qi Sun, Lu Zhang, Yibo Lin, Iris Hui-Ru Jiang, Bei Yu, David Z. Pan, “OpenMPL: An Open Source Layout Decomposer”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 40, no. 11, pp. 2331–2344, 2021. (paper)

  • [J56] Guyue Huang, Jingbo Hu, Yifan He, Jialong Liu, Mingyuan Ma, Zhaoyang Shen, Juejian Wu, Yuanfan Xu, Hengrui Zhang, Kai Zhong, Xuefei Ning, Yuzhe Ma, Haoyu Yang, Bei Yu, Huazhong Yang, Yu Wang, “Machine Learning for Electronic Design Automation: A Survey”, ACM Transactions on Design Automation of Electronic Systems (TODAES), vol. 25, no. 5, 2021. (paper)

2020


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, Nov. 5–8, 2012. (paper) (Embedded Tutorial paper)


2011

2010

2009



Books / Book Chapters

 

[B4] Haoyu Yang, Yibo Lin, Bei Yu, “Machine Learning for Mask Synthesis and Verification”, in Machine Learning Applications in Electronic Design Automation, Mark Ren eds., Springer, 2022. (paper)

 

[B3] Shiyan Hu, Bei Yu, “Big Data Analytics for Cyber-Physical Systems”, Springer, 2020.

 

[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.