Large-Scale FPGA implementations of Machine Learning Algorithms



FPGA implementations of machine learning algorithms have been shown to be extremely efficient when the problem fits entirely on the FPGA but it remains a challenge to scale to problems of interest to industry. In this talk, our recent research on how to increase the capacity of existing approaches will be described.

  Date and Time




  • City University of HK
  • G6302, 6/F, Green Zone, Yeung Kin Man Academic Building
  • Hong Kong, Guangdong
  • China
  • Dr. Ray C.C. Cheung, Department of Electronic Engineering, CityU

    Tel: 3442 9849, Fax:3442 0562


Prof. Philip Leong


Philip Leong received the B.Sc., B.E. and Ph.D. degrees from the University of Sydney. In 1993 he was a consultant to ST Microelectronics in Milan, Italy working on advanced flash memory-based integrated circuit design. From 1997-2009 he was with the Chinese University of Hong Kong. He is currently Professor of Computer Systems in the School of Electrical and Information Engineering at the University of Sydney, Senior Visitor Scholar at Fudan University, Visiting Professor at Imperial College, Visiting Professor at Harbin Institute of Technology, and Chief Technology Advisor to ClusterTech.

Address:School of Electrical and Information Engineering University of Sydney, , Sydney, New South Wales, Australia