Speaker: Tony Chan Carusone
Location: DSI Conference Room (1406 Northwest Corner)
Title: Scaling AI with Chiplet-Based Systems
Abstract: In the rapidly evolving landscape of artificial intelligence, chiplets are emerging as a transformative technology, paving the way for the next generation of AI systems. Chiplets permit the integration of more processing power within a single package and allow for new connectivity solutions so that thousands of AI accelerators can work as a cohesive unit. Optical connectivity, facilitated by chiplets, offers high-speed data transmission with lower power consumption, crucial for handling the massive data loads in AI applications. The emerging chiplet ecosystem, underwritten by high-performance die-to-die interfaces, is throwing open the doors of innovation and facilitating the next wave of AI scaling.
Bio: Professor Chan Carusone teaches and researches integrated circuits and systems. He graduated from U of T’s Engineering Science program, receiving the Governor General’s Silver Medal in 1997. He obtained his PhD in the The Edward S. Rogers Sr. Department of Electrical & Computer Engineering in 2002 and joined the faculty immediately thereafter. He co-authored the classic textbooks Analog Integrated Circuit Design and Microelectronic Circuits, the latter of which is the best-selling engineering textbook of all time.
Chan Carusone and his graduate students have received nine best-paper awards at leading IEEE conferences in the areas of chip-to-chip communication, optical transceivers, analog-to-digital conversion and high-speed clocking. He has served on the editorial boards and technical program committees of practically all the world’s leading journals and conferences on integrated circuit design. His research group is currently designing nanoscale planar and FinFET CMOS integrated circuits to tackle problems in high-speed digital communication, imaging and machine learning.