Cheng Liu

Cheng Liu

My research interests include computer architecture, integrated circuits, and EDA.

Home

I am an associate professor in State Key Laboratory of Processors (SKLP), Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). I got my B.Eng degree and M.Eng degree from Harbin Institute of Technology, and Ph.D degree from The University of Hong Kong advised by Prof. Hayden So in 2016. I worked as a research fellow in National University of Singapore from 2016 to 2018, and thereafter, I joined ICT as an associate professor. My current research interest focuses on domain specific architecture and system, intelligent IC design and EDA tools.

Vancancies

I am looking for self-motivated intern students. Students with EE and CS background are preferred. It is possible to work fully remotely. Check the topics in the following list and contact me if you are interested.

  • Domain-specific architecture and system
  • Intelligent SoC design
  • Intelligent EDA tools
  • In-storage big data processing system

News

  • [Jun 2020] Shengwen Liang and Rick Lee won the Third Prize (FPGA Track) of the 2020 IEEE Low-Power Computer Vision Challenge (LPCVC).
  • [Jul 2022] Haitong Huang, Erjing Luo, and Cangyuan Li in my group got the Third Place in DAC’22 SDC.
  • [Jan 2023] Our work “EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph Neural Networks” won the Best Paper Award of TC’21.
  • [Jun 2023] Congratulations! Haitong Huang, Erjing Luo, and Guoyu Li got the Second Place in DAC’23 SDC.
  • [Nov 2023] A HW/SW co-design framework for mixed-precision neural network acceleration on FPGAs (DeepBurning-MixQ) is accepted by ICCAD’23. We are adding LLM support to enable more intelligent code generation. The code is open sourced on github and welcome to try it.
  • [Mar 2024] A multi-resolution fault injection framework for deep learning is accepted by TVLSI’24. It is well documented and validated sufficiently, and provides many convenient evaluation features that are typically required in fault-tolerant deep learning study. Check it on github.

Fundings

  • HW/SW platform for intelligent cross-layer design and optimization of processors, 11 000 000￥, xdb(2024-2028)
  • Natural weather disturbed image generation for remote sensing, 500 000￥, XXX(2023-2024)
  • AI assisted DSA design automation, 300 000￥, SKLP(2023-2024)
  • Automatic Cross-Layer DSA Design and Optimization, 1 600 000￥, National Key Research and Development Program of China(2023-2025)
  • Intelligent In-Storage Big Data Processing System, 1 300 000￥, 1XX(2023-2024)
  • Fault-tolerant Deep Learning Toolchain for COTS Devices, 300 000￥, XXX(2023)
  • Elastic Fault-tolerant Deep Learning Processor Design, 570 000￥, NSFC(2022-2025)
  • Customized Energy-efficient Graph Processing Acceleration on FPGAs, 300 000￥, NSFC(2020-2022)
  • Fault-tolerant Deep Learning Processor Design Automation, 300 000￥, SKLCA(2021-2022)

Talks

  • 异构硬件加速器设计、优化以及编程, 高性能异构计算与人工智能优化论坛，CCF-HPC，2023
  • 基于计算存储器的图处理系统设计, 面向复杂图计算应用的新型高能效体系结构论坛，CNCC，2022
  • 容错深度学习处理器微结构设计，集成电路设计与自动化学术会议(CCF-DAC), 2021
  • DeepBurning2.0: An Automatic End-to-end Neural Network Acceleration System on FPGAs, 华南理工大学，软件学院, 2019

Services

  • PC for DFT’22, FPT’22, ATS’23, FPT’23, DFT’23, ITC’22, ITC’23, NIPS’23, ICLR’24, FCCM’24, ICML’24
  • Review for TC, TPDS, TCAD. TVLSI, TETC, JETC, JSA, TNNLS

Graduated Students

  • Erjing Luo (Intern from Beijing Institute of Technology, Mphil in University of Alberta)
  • Miaoxin Wang (Intern from Harbin Institute of Technology, Master student in Nanjing University)
  • Jinming Zhao (Intern from Wuhan University, PhD candidate in the University of Hong Kong)
  • Zhiyu Zhu (Intern from Harbin Institute of Technology, CETC 47)
  • Cheng Chu (Intern from Hefei University of Technology, PhD candidate in Indiana University Bloomington)
  • Meng He (Intern from Hefei University of Technology, 字节跳动)
  • Ziyang Zhu (Intern from Hefei University of Technology, 紫光展锐)
  • Qiang Zhang (Master Student, 快手)
  • Kouzi Xing (Intern from Hefei University of Technology, 商汤科技)
  • Li Li (Intern from Hefei University of Technology, 京东)
  • Kexin Chu (Intern from Hefei University of Technology, 百度)
  • Kaijie Tu (Intern from Hefei University of Technology, 计算所)
  • Chang Shi (Master student, Alibaba)
  • Peibin Wu (Master student, MSRA)