RRAM-enabled and Application-Specific Co-Designed AI Accelerators
ID:17 View Protection:ATTENDEE Updated Time:2021-12-09 11:22:32 Hits:650 Keynote speech

Start Time:2021-12-11 09:45(Asia/Shanghai)

Duration:50min

Session:P 开幕式及主旨报告 » P1开幕式和主旨报告

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Abstract
We will give an overview of some recent results on 3D integration of CMOS and memristive memory arrays and demonstrate its potential of offering very high memory density and bandwidth at manageable power dissipation, and enabling new memory-centric computing paradigms for AI applications.
It has been recognized that such resistive memory cells still suffer from multiple limitations including high energy consumption for programming, limited endurance, and large cycle-to-cycle and device-to-device variations. We will highlight research directions and some recent solutions addressing these limitations.
Finally, we will discuss recent development and research opportunities of an application-specific co-design framework which closely integrates application-specific neural network search, hardware-friendly network compression and NN-aware architecture design for iterative co-optimization.
Keywords
Speaker
ChengK.-T. Tim
Professor Hong Kong University of Science and Technology

K.-T. Tim Cheng received his Ph.D. in EECS from the University of California, Berkeley in 1988. He has been serving as Dean of Engineering and Chair Professor of ECE and CSE at Hong Kong University of Science and Technology (HKUST) since May 2016. He worked at Bell Laboratories from 1988 to 1993 and joined the faculty at Univ. of California, Santa Barbara in 1993 where he was the founding director of UCSB’s Computer Engineering Program (1999-2002), Chair of the ECE Department (2005-2008) and Associate Vice Chancellor for Research (2013-2016). His current research interests include AI accelerator design, EDA, computer vision, and medical image analysis. He has recently led the founding of the AI Chip Center for Emerging Smart Systems (ACCESS) which is a multidisciplinary center aims to advance IC design to help realize ubiquitous AI applications in society.

Cheng, an IEEE fellow and a fellow of Hong Kong Academy of Engineering Sciences a, received 10+ Best Paper Awards from various IEEE and ACM conferences and journals. He has also received UCSB College of Engineering Outstanding Teaching Faculty Award, Pan Wen Yuan Outstanding Research Award, 2020,  and Fellow of School of Engineering, The University of Tokyo. He served as Editor-in-Chief of IEEE Design and Test of Computers and was a board member of IEEE Council of Electronic Design Automation’s Board of Governors and IEEE Computer Society’s Publication Board.

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Important Date
  • Conference Date

    Dec 11

    2021

    to

    Dec 12

    2021

  • Aug 18 2021

    Registration deadline

Sponsored By
中国计算机学会
Organized By
中国计算机学会容错计算专业委员会
同济大学软件学院
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