Northwestern University

May
9
Wed 2:00 PM

EECS Distinguished Speaker: Prof. Naresh Shanbhag, Jack S. Kilby Professor of ECE at University of Illinois Urbana-Champaign, "Bringing Artificial Intelligence to the Edge – A Shannon-inspired Approach"

Prof. Naresh Shanbhag

When: Wednesday, May 9, 2018
2:00 PM - 3:00 PM  

Where: Ford Motor Company Engineering Design Center, ITW Room, 2133 Sheridan Road, Evanston, IL 60208 map it

Audience: Faculty/Staff - Student - Public - Post Docs/Docs - Graduate Students

Contact: Lana Kiperman   847.467.0028

Group: Electrical Engineering & Computer Science

Category: Lectures & Meetings

Description:

The EECS Department welcomes Prof. Naresh Shanbhag, Jack S. Kilby Professor of ECE at University of Illinois Urbana-Champaign.

Shanbhag will present a talk entitled "Bringing Artificial Intelligence to the Edge – A Shannon-inspired Approach" on Wednesday, May 9 at 2:00 PM in Ford ITW Room.

Abstract: Much of AI today is deployed in the Cloud primarily due to the high complexity of machine learning algorithms. Realizing inference functionality on sensory Edge devices requires one to find ways to operate at the other edge, i.e., at the limits of energy efficiency, latency, and accuracy, in nanoscale semiconductor technologies. This talk will describe the Shannon-inspired statistical computing framework developed by researchers in the SONIC Center (2013-17), to accomplish this objective. This framework comprises low signal-to-noise ratio (SNR) circuit fabrics (the channel) with engineered error statistics, coupled with efficient techniques to compensate for computational errors (encoder and decoder). A low SNR circuit fabric referred to as deep in-memory architecture (DIMA) will be described. DIMA breaches the long-standing “memory wall” in von Neumann architectures by embedding analog computations in the periphery of the memory array (see https://spectrum.ieee.org/computing/hardware/to-speed-up-ai-mix-memory-and-processing) thereby achieving >100X energy-delay-product gains in laboratory prototypes over custom digital architectures implementing the same inference function. The strong systems-to-devices connection inherent in Shannon-inspired statistical computing creates an opportunity for researchers in machine learning, computer architecture, integrated circuits, and nanoscale devices, to work together to design intelligent machines of the future. The talk will end with a discussion of future directions.

Bio: Prof. Naresh Shanbhag is the Jack S. Kilby Professor of ECE at University of Illinois-Champaign. He teaches and conducts research in the area of integrated circuits and systems for communications and computing. Particular areas of interest are: energy-efficient digital/mixed-signal IC design, DSP and communication systems design, and statistical information processing systems.

Hosted by EECS Prof. Jie Gu

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