Zhenman Fang
Assistant Professor

Computer Engineering Option
School of Engineering Science
Simon Fraser University
8888 University Drive | ASB 9837
Burnaby, BC V5A 1S6, Canada

Email: zhenman [at] sfu [dot] ca

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News

  • PhD and MASc opening: Dr. Fang is actively looking for PhD and Master students to join his HiAccel lab. Please find more details in the recruiting page. For SFU students who are interested in joining HiAccel lab, the best way is to take the ENSC 453/894 course in Fall on "Programming for Heterogeneous Computing System" and stand out (A+) in the class.
  • Here is a nice, high-level introduction to FPGAs, one of the key components of our research: Architecture All Access: Modern FPGA Architecture. This talk is given by Intel, but most of the contents apply to both Intel and AMD/Xilinx FPGAs.
  • Reference letter request: I only provide recommendation letters for undergraduate or graduate students whom I know well, i.e., (1) with whom I have worked in research, or (2) who have received an A+ in my courses and had significant face-to-face interaction with me.
  • Paper submission: Dr. Fang is serving as the Program Chair for RAW 2024 and Program Co-Chair for PacRim 2024. Welcome to submit.
  • Dec 2023, one paper accepted by ICASSP 2024. The paper is on "Efficient Learned Image Compression with Selective Kernel Residual Module and Channel-wise Causal Context Model". Congrats to Haisheng (co-supervised with Prof. Jie Liang)!
  • Dec 2023, one paper accepted by DCC 2024. The paper is on "Learned Image Compression with Dual-Branch Encoder and Conditional Information Coding". Congrats to Haisheng (co-supervised with Prof. Jie Liang)!
  • Dec 2023, one paper accepted by FPGA 2024. The paper is on "HiSpMV: Hybrid Row Distribution and Vector Buffering for Imbalanced SpMV Acceleration on FPGAs". It received the highest review score among all FPGA 2024 submissions, tied with two other papers. Congrats to Manoj and Xingyu!
  • Dec 2023, Dr. Fang is invited to serve on the FCCM 2024 TPC, welcome to submit!
  • Nov 2023, one visiting PhD and one postdoc join HiAccel lab! Welcome, Qilin and Haisheng!
  • Nov 2023, Dr. Fang gives an invited (virtual) talk on "Software-Programmable Accelerator-Centric Systems" at City University of Hong Kong!
  • Oct 2023, one paper accepted by FPT 2023 Journal Track (ACM TRETS). The paper is on "HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks". This is a work in collaboration with Prof. Jie Lei's group from Xidian University (lead).
  • Oct 2023, Dr. Fang is invited to serve as the PacRim 2024 Program Co-Chair, welcome to submit!
  • Oct 2023, Dr. Fang is invited to serve on the ARC 2024 organizing committee, welcome to submit!
  • Oct 2023, Dr. Fang is invited to serve on the DAC 2024 TPC, welcome to submit!
  • Sept 2023, one PhD and two MASc students join HiAccel lab! Welcome, Ahmad, Akhil, and Philip!
  • Aug 2023, Mitacs Globalink Research Internship positions available in the HiAccel team for Summer 2024. The project is for international senior undergraduate students. Please apply by September 21, 2023 at 1 pm PT. One project will be on "Big Data Acceleration on FPGAs" and another project will be on "Hardware/Software Codesign for Deep Learning Acceleration". More details on the project can be found here. Just filter the projects with Host University as "Simon Fraser University - Burnaby" and Professor's Last Name as "Fang"!
  • Aug 2023, Dr. Fang is invited to serve on the DATE 2024 TPC, welcome to submit!
  • Aug 2023, one paper accepted by TRETS. The paper is on "CHIP-KNNv2: A Configurable and High-Performance K-Nearest Neighbors Accelerator on HBM-based FPGAss". Congrats to Kenny, Alec, and Kartik!
  • Jul 2022, Dr. Fang is invited to serve on the FPGA 2024 TPC, welcome to submit!
  • Jul 2023, one paper accepted by TRETS. The is a collaboration paper with UCLA team (lead) on "TAPA: A Scalable Task-Parallel Dataflow Programming Framework for Modern FPGAs with Co-Optimization of HLS and Physical Design", congrats to Xingyu and Moazin!
  • Jul 2023, Dr. Fang visits AMD/Xilinx and Futurewei, and gives a talk on "Software-Programmable Accelerator-Centric Systems"!
  • Jul 2023, Together with Prof. Yanzhi Wang (Northeastern University) and Dr. Linghao Song (UCLA), Dr. Fang is co-organizing the DAC-ROAD4NN 2023 Workshop for the fourth year. Welcome to attend our workshop at DAC 2023, Jul 9, Sunday, San Francisco, CA.
  • More News

Bio

Dr. Zhenman Fang is a Tenure-Track Assistant Professor in School of Engineering Science (Computer Engineering Option) and an Associate Member in School of Computing Science, Simon Fraser University, Canada. Zhenman founded and directs the HiAccel lab. He is also a member of SFU Systems Group and SFU Institute for Neuroscience and Neurotechnology.

Zhenman's recent research focuses on customizable computing with software-defined hardware acceleration, which aims to sustain the ever-increasing performance, energy-efficiency, and reliability demand of important application domains in post-Moore’s law era. It spans the entire computing stack, including emerging application characterization and acceleration (including machine learning, big data analytics, computational genomics, and high-performance computing), novel accelerator-rich and near-data computing architecture designs, and corresponding programming, runtime, and tool support. Zhenman has published over 50 papers in top conferences and journals and two US patents, including two best paper awards (TCAD 2019 Donald O. Pederson best paper award and MEMSYS 2017), two best paper nominees (HPCA 2017 and ISPASS 2018), a top paper highlighted in the FPGA 2021 Special Issue in ACM TRETS, a top paper received the highest review score among all FPGA 2024 submissions, and an invited paper from Proceedings of the IEEE 2019. His research has also been recognized with a NSERC (Natural Sciences and Engineering Research Council of Canada) Alliance Award (2020), a CFI JELF (Canada Foundation for Innovation John R. Evans Leaders Fund) Award (2019), a Xilinx University Program Award (2019), a Team Award from Xilinx Software and IP Group (2018), and a Postdoc Fellowship from UCLA Institute for Digital Research and Education (2016-2017).

Before joining SFU, Zhenman worked in the Xilinx SDx (now rebranded as AMD/Xilinx Vitis) group at San Jose as a Staff Software Engineer from Sept 2017 to Mar 2019. At Xilinx, he worked on the topic of accelerator-rich architectures and systems, which is the major focus of his postdoc research at UCLA. From Jul 2014 to Sept 2017, Zhenman was a postdoc in Department of Computer Science, UCLA, under the supervision of Prof. Jason Cong and Prof. Glenn Reinman. While at UCLA, he was also a member of the NSF/Intel funded multi-university Center for Domain-Specific Computing (CDSC) and SRC/DARPA funded multi-university Center for Future Architectures Research (C-FAR). Zhenman earned his Ph.D degree in Jun 2014 from School of Computer Science, Fudan University, China, under the supervision of Prof. Binyu Zang. He also spent the last 15 months of his PhD study visiting Department of Computer Science and Engineering, University of Minnesota at Twin Cities, under the supervision of Prof. Pen-Chung Yew.

Zhenman is a Professional Engineer in the province of British Columbia (registered with APEGBC) and a Senior Member of IEEE.


Recent Services

  • Organizing: PacRim 2024 Program Co-Chair, RAW 2024 Program Chair, ARC 2024 Publicity Co-Chair, FCCM 2023 Demo Night Co-Chair, FPL 2022 Publicity Chair, FCCM 2022 Workshop Chair and Travel Awards Chair, DAC-ROAD4NN 2020-2023 Organizing Chair, ASAP 2021 Special Session Chair
  • 2024 TPC: FPGA, FCCM, DAC, DATE, RAW (Program Chair)
  • 2023 TPC: FPGA, FCCM, FPL, FPT, DAC, HPCA, ISCA (ERC), MICRO (Light Load)
  • 2022 TPC: FPGA, FCCM, FPL, FPT, DAC, DATE, MICRO, ISCA (ERC)
  • 2021 TPC: FPGA, FPT, DAC, DATE, IPDPS, ICCD, ASAP, ISCA (ERC), MICRO (ERC)
  • More Services

Research Interests

  • Emerging workload characterization and acceleration: especially for machine learning, big data analytics, computational genomics, image and video processing, and high-performance computing
  • Computer architecture: especially for heterogeneous and energy-efficient accelerator-rich architectures (ARAs), multicore and many-core architectures, memory systems and near data acceleration
  • Programming, automation, and compiler support: especially programming, automation, and compiler support for the above computer architectures
  • Big data computing system: especially for enabling FPGA accelerators in datacenter
  • Performance evaluation: especially for architectural simulation, benchmarking, prototyping, and GPU-FPGA comparison
  • Reliability for hardware accelerators: especially for learning-based hardware reliability modeling and robustness for machine learning accelerators

Awards

Dec 2023
FPGA 2024 Paper with the Highest Review Score
May 2023
Institute of Electrical and Electronics Engineers (IEEE) Senior Member
Dec 2022
FPGA 2021 Paper Highlighted in ACM TRETS Special Issue
Oct 2020
Natural Sciences and Engineering Research Council of Canada (NSERC) Alliance Award
Oct 2019
Xilinx University Program Award
Sept 2019
Canada Foundation for Innovation John R. Evans Leaders Fund (CFI JELF) Award
May 2019
TCAD 2019 Donald O. Pederson Best Paper Award, IEEE Council on Electronic Design Automation
Dec 2018
Team Award in Xilinx Software and IP Group (1000+ people group)
Jul 2018
Outstanding Reviewer, Elsevier Journal of Parallel and Distributed Computing (JPDC)
Apr 2018
ISPASS 2018 Best Paper Nominee
Oct 2017
MEMSYS 2017 Best Paper Award
Aug 2017
Outstanding Reviewer, Integration, the Elsevier VLSI Journal
Aug 2017
Outstanding Reviewer, Elsevier Microprocessors and Microsystems (MICPRO)
Feb 2017
HPCA 2017 Best Paper Nominee
Dec 2016
Best Demo Award (3rd Place out of 49 Demos) at C-FAR 2016 Annual Review
Jun 2016
Outstanding Reviewer, Elsevier Journal of Parallel and Distributed Computing (JPDC)
May 2016
UCLA Institute for Digital Research and Education (IDRE) 2016-2017 Postdoc Fellowship
Nov 2012
China National Scholarship for PhD Students, Ministry of Education of China