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

  • 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 462/894 course on "Programming for Heterogeneous Computing System" and stand out in the class.
  • Nov 2021, one paper accepted by FPGA 2022. The paper is on "FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization", congrats to Alec. This is a work in collaboration with Prof. Xue Lin's group from Northeastern University (lead).
  • Nov 2021, one paper accepted by TRETS. The paper is on "Quick-Div: Rethinking Integer Divider Design for FPGA-based Soft-Processors", congrats to Eric and Alec!
  • Nov 2021, one paper accepted by DATE 2022. The paper is on "FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions", congrats to Behnam (Research Associate, co-supervised with Prof. Lesley Shannon)!
  • Nov 2021, Dr. Fang publishes a short article "What is Customizable Computing" in ACM SIGDA newsletter.
  • Nov 2021, Dr. Fang is invited to serve on the FCCM 2022 TPC, welcome to submit!
  • Oct 2021, Dr. Fang is invited to serve on the ISCA 2022 ERC, welcome to submit!
  • Oct 2021, Dr. Fang is invited to serve on the DAC 2022 TPC, welcome to submit!
  • Sept 2021, Dr. Fang is invited to serve on the FCCM 2022 organizing committee, welcome to submit!
  • Sept 2021, Dr. Fang is invited to serve on the DATE 2022 TPC, welcome to submit!
  • Sept, 2021, the preprint of our survey paper "Programming and Synthesis for Software-defined FPGA Acceleration: Status and Future Prospects" is now available on the ACM Digital Library. This is a work in collaboration with Prof. Zhiru Zhang's group from Cornell University (lead) and Dr. Hongbo Rong from Intel. Please check it out.
  • Sept 2021, Dr. Fang has been registered as a Professional Engineer with Engineers and Geoscientists BC (EGBC)!
  • Aug 2021, we have open sourced our SyncNN framework that supports the evaluation and acceleration of spiking neural networks on FPGAs, written in High-Level Synthesis C/C++. Check it out here.
  • Aug 2021, two MASc students join HiAccel lab! Welcome, Moazin and Junzhe!
  • Aug 2021, Dr. Fang is invited to serve on the FPGA 2022 TPC, welcome to submit!
  • Jul 2021, Dr. Fang is co-organizing the 2nd ROAD4NN Workshop (Research Open Automatic Design for Neural Networks), co-located with DAC 2021, welcome to submit!
  • May 2021, one full paper and one short paper accepted by FPL 2021. The full paper is on "SyncNN: Evaluating and Accelerating Spiking Neural Networks on FPGAs", congrats to Sathish! The short paper is on "MAPLE: A Machine Learning based Aging-Aware FPGA Architecture Exploration Framework", congrats to Behnam (Research Associate, co-supervised with Prof. Lesley Shannon)!
  • Apr 2021, together with Christian Pilato, Yuko Hara-Azumi, Jim Hwang, Dr. Fang is organizing a TODAES special issue on High-Level Synthesis for FPGA: Next-Generation Technologies and Applications. Welcome to submit!
  • 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. Zhenman is also a member of SFU Systems Group.

Zhenman's recent research focuses on customizable computing with specialized 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, computational genomics, and big data analytics), novel accelerator-rich and near-data computing architecture designs, and corresponding programming, runtime, and tool support. Zhenman has published over 30 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), and an invited paper from Proceedings of the IEEE 2019. His research has also been recognized with a Natural Sciences and Engineering Research Council of Canada (NSERC) Alliance Award (2020), a Canada Foundation for Innovation John R. Evans Leaders Fund (CFI JELF) 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 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).


Recent Services

  • Organizing: FCCM 2022 Panel Chair, ROAD4NN 2021 Organizing Chair, ASAP 2021 Special Session Chair
  • 2022 TPC: DAC, DATE, FPGA, FCCM, ISCA (ERC)
  • 2021 TPC: DAC, DATE, FPGA, IPDPS, ICCD, FPT, ASAP, ISCA (ERC), MICRO (ERC)
  • More Services

Research Interests

  • Emerging workload characterization and acceleration: especially for computational genomics, big data analytics, machine learning, 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 and compiler optimization: especially for improving memory system performance, programming and compiler support for the above architectures
  • Big data computing system: especially for enabling FPGA accelerators in datacenter
  • Performance evaluation and design automation: especially for architectural simulation, benchmarking, prototyping, and GPU-FPGA comparison
  • Reliability for hardware accelerators: especially for machine learning based reliability modeling for accelerators, and reliability for machine learning accelerators

Awards

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