Lixin Liu

Postdoctoral Fellow

 

Department of Computer Science and Engineering
The Chinese University of Hong Kong

 

lxliu [at] cse.cuhk.edu.hk
kerryliu1997 [at] gmail.com

 

[Github] | [Google Scholar] | [Linkedin]

Biography

I am a Postdoctoral Fellow at The Chinese University of Hong Kong. I obtained my Ph.D. degree from CUHK in 2023 under the supervision of Prof. Evangeline F.Y. Young, and my B.Eng. degree from South China University of Technology in 2019. My earlier research focused on GPU-accelerated VLSI EDA. Currently, I am primarily working on LLM algorithm-system co-optimization and LLM-assisted combinatorial optimization.

Selected Works

ExactMap: Enhancing Delay Optimization in Parallel ASIC Technology Mapping

Zhenxuan Xie, Lixin Liu, Tianji Liu, Evangeline F.Y. Young

International Conference On Computer Aided Design (ICCAD) 2025 (Best Paper Award Nomination)

Hybrid Modeling and Weighting for Timing-driven Placement with Efficient Calibration

Bangqi Fu, Lixin Liu, Martin D.F. Wong, Evangeline F.Y. Young

International Conference On Computer Aided Design (ICCAD) 2024

[Code]

Parmesan: Efficient Partitioning and Mapping Flow for DNN Training on General Device Topology

Lixin Liu, Tianji Liu, Bentian Jiang, Evangeline F.Y. Young

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) 2024

[Code] | [Additional Results]

Xplace: An Extremely Fast and Extensible Placement Framework

Lixin Liu, Bangqi Fu, Shiju Lin, Jinwei Liu, Evangeline F.Y. Young, Martin D.F. Wong

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) 2024

[Code]

CoPlace: Coherent Placement Engine with Layout-aware Partitioning for 3D ICs

Bangqi Fu, Lixin Liu, Yang Sun, Wing-Ho Lau, Martin D.F. Wong, Evangeline F.Y. Young

ACM/IEEE Asia and South Pacific Design Automation Conference Technical Program (ASP-DAC) 2024 (Best Paper Award Nomination)

[Slides]

Xplace: An Extremely Fast and Extensible Global Placement Framework

Lixin Liu, Bangqi Fu, Martin D.F. Wong, Evangeline F.Y. Young

ACM/IEEE Design Automation Conference (DAC) 2022

[Code] | [Slides]

Neural-ILT: Migrating ILT to Neural Networks for Mask Printability and Complexity Co-optimization

Bentian Jiang, Lixin Liu, Yuzhe Ma, Hang Zhang, Bei Yu, Evangeline F.Y. Young

International Conference On Computer Aided Design (ICCAD) 2020

[Code] | [Slides]

Thesis

When Placement Meets GPU: GPU-Accelerated VLSI Placement and Device Placement for GPUs [Thesis]

Honors & Awards