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Title: Energy-efficient Circuits and System Architectures to Enable Intellignece and the Edge of the Cloud
Committee:
Dr. Raychowdhury, Advisor
Dr. Lim, Chair
Dr. Romberg
Abstract:
The objective of the proposed research is to enable computation close to the sensor. Internet of Things (IoT) devices are collecting a large amount of data for video processing, monitoring health etc. Transmitting the data from the sensor to the cloud requires a large aggregate bandwidth. The objective of the proposed research is to leverage advances in machine learning to perform in-sensor computation, thus reducing the transmission bandwidth, preserving data privacy and enabling low-power operation. The proposed research demonstrates a system design and IC designs to achieve energy efficiency. As a system prototype, we demonstrate a light-powered always ON gesture recognition system. As circuit innovations, we demonstrate voltage and time based matrix multiplying ADCs (MMADCs), compressive sensing ADCs (CS-ADCs) along with measurement results. The proposed time based MMADC is digitally synthesizable, can operate at a supply as low supply as 0.4V and demonstrates higher energy efficiency compared to the state of the art designs.