Efficient Computing for Resource-Constrained Cyber-Physical Systems
Date: 2023/05/26 - 2023/05/26
Academic Seminar: Efficient Computing for Resource-Constrained Cyber-Physical Systems
Speaker: An Zou, Assistant Professor, University of Michigan-Shanghai Jiao Tong University Joint Institute
Time: 10:00 - 11:30, May 26, 2023 (Beijing Time)
Location: CIMC Auditorium (Room 300), JI Longbin Building
With the rapid advancement of computing technology, cyber-physical systems like drones, self-driving cars, and mobile cognitive robots have made remarkable progress in terms of multifunctionality and miniaturization. As a result, these resource-constrained cyber-physical systems (RCCPSs) are now capable of carrying out diverse tasks in environments with limited resources. Consequently, the computing systems powering RCCPSs must achieve high efficiency and scalability. First and foremost, it is essential for these computing systems to be power-efficient while delivering optimal performance. This requirement is particularly crucial as they need to handle complex algorithms for learning-based perception and AI-driven decision-making within the constraints of a fixed amount of onboard energy. Moreover, scalability is of utmost importance, necessitating the ability to expand the current computing system and its components both horizontally (with additional resources) and vertically (by incorporating emerging advanced technology).
To achieve efficient and scalable computing systems in RCCPSs, we broadly investigates a set of techniques and solutions via a bottom-up layered approach. This layered approach leverages the characteristics of each system layer (e.g., the circuit, architecture, and operating system layers) and their interactions to discover and explore the optimal system tradeoffs among performance, efficiency, and scalability.
An Zou is an Assistant Professor at UMJI in the Shanghai Jiao Tong University. His research focuses on computer architecture, processor low-power design, and embedded systems. Dr. An Zou received his Ph.D. degree in Electrical Engineering from Washington University in St. Louis in 2021 and his M.S. and B.S. degrees from Harbin Institute of Technology (HIT) in 2015 and 2013. He led or participated in several research projects from the National Natural Science Foundation of China, the National Science Foundation, the Semiconductor Research Corporation, and industry companies. His work has been extensively published and recognized at top-tier conferences and journals, including MICRO, DAC, ICCAD, AAAI, RTAS, TCAD, TPDS, and TACO. He was a recipient of Shang A. Richard Newton Young Student Fellow Award and the Best Paper Nominations at DAC 2017 and MLCAD 2020.