C-BRIC JUMP e-Workshop

Event Date: December 8, 2020
Time: 11:00am (ET) / 8:00am (PT)
Priority: No
School or Program: Electrical and Computer Engineering
College Calendar: Show
Kaushik Roy, Purdue University
Re-engineering computing with Neuro-inspired Learning: Algorithms, Architecture, and Devices

Abstract: Advances in machine learning, notably deep learning, have led computers to match or surpass human performance in several cognitive tasks including vision, speech and natural language processing. However, implementation of neural algorithms in conventional "von-Neumann" architectures are several orders of magnitude more area and power expensive than the biological brain. Hence, we need fundamentally new approaches to sustain the exponential growth in performance at high energy-efficiency. Exploring the new paradigm of computing necessitates a multi-disciplinary approach: exploration of new learning algorithms inspired from neuroscientific principles, developing network architectures best suited for such algorithms, new hardware techniques to achieve orders of improvement in energy consumption, and nanoscale devices that can closely mimic the neuronal and synaptic operations. In this talk, I will present our recent work on spike-based learning to achieve high energy efficiency with accuracy comparable to that of standard analog deep-learning techniques. Input coding from DVS cameras has been used to develop energy efficient hybrid SNN/ANN networks for optical flows, gesture recognition, and language translation. Additionally, we propose probabilistic neural and synaptic computing platforms that can leverage the underlying stochastic device physics of spin-devices. System-level simulations indicate ~100x improvement in energy consumption for such spintronic implementations over a corresponding CMOS implementation across different computing workloads. Complementary to the above device efforts, we have explored different local/global learning algorithms including stochastic learning with one-bit synapses that greatly reduces the storage/bandwidth requirement while maintaining competitive accuracy, and adaptive online learning that efficiently utilizes the limited memory and resource constraints to learn new information without catastrophically forgetting already learnt data.

Bio: Kaushik Roy received B.Tech. degree in electronics and electrical communications engineering from the Indian Institute of Technology, Kharagpur, India, and Ph.D. degree from the electrical and computer engineering department of the University of Illinois at Urbana-Champaign in 1990. He was with the Semiconductor Process and Design Center of Texas Instruments, Dallas, where he worked on FPGA architecture development and low-power circuit design. He joined the electrical and computer engineering faculty at Purdue University, West Lafayette, IN, in 1993, where he is currently Edward G. Tiedemann Jr. Distinguished Professor. He also the director of the center for brain-inspired computing (C-BRIC) funded by SRC/DARPA. His research interests include neuromorphic and emerging computing models, neuro-mimetic devices, spintronics, device-circuit-algorithm co-design for nano-scale Silicon and non-Silicon technologies, and low-power electronics. Dr. Roy has published more than 700 papers in refereed journals and conferences, holds 18 patents, supervised 85 PhD dissertations, and is co-author of two books on Low Power CMOS VLSI Design (John Wiley & McGraw Hill).

Dr. Roy received the National Science Foundation Career Development Award in 1995, IBM faculty partnership award, ATT/Lucent Foundation award, 2005 SRC Technical Excellence Award, SRC Inventors Award, Purdue College of Engineering Research Excellence Award, Humboldt Research Award in 2010, 2010 IEEE Circuits and Systems Society Technical Achievement Award (Charles Desoer Award), Distinguished Alumnus Award from Indian Institute of Technology (IIT), Kharagpur, Fulbright-Nehru Distinguished Chair, DoD Vannevar Bush Faculty Fellow (2014-2019), Semiconductor Research Corporation Aristotle award in 2015, and best paper awards at 1997 International Test Conference, IEEE 2000 International Symposium on Quality of IC Design, 2003 IEEE Latin American Test Workshop, 2003 IEEE Nano, 2004 IEEE International Conference on Computer Design, 2006 IEEE/ACM International Symposium on Low Power Electronics & Design, and 2005 IEEE Circuits and system society Outstanding Young Author Award (Chris Kim), 2006 IEEE Transactions on VLSI Systems best paper award, 2012 ACM/IEEE International Symposium on Low Power Electronics and Design best paper award, 2013 IEEE Transactions on VLSI Best paper award. Dr. Roy was a Purdue University Faculty Scholar (1998-2003). He was a Research Visionary Board Member of Motorola Labs (2002) and held the M. Gandhi Distinguished Visiting faculty at Indian Institute of Technology (Bombay) and Global Foundries visiting Chair at National University of Singapore. He has been in the editorial board of IEEE Design and Test, IEEE Transactions on Circuits and Systems, IEEE Transactions on VLSI Systems, and IEEE Transactions on Electron Devices. He was Guest Editor for Special Issue on Low-Power VLSI in the IEEE Design and Test (1994) and IEEE Transactions on VLSI Systems (June 2000), IEE Proceedings -- Computers and Digital Techniques (July 2002), and IEEE Journal on Emerging and Selected Topics in Circuits and Systems (2011). Dr. Roy is a fellow of IEEE.