Ishan Thakkar

University of Kentucky

Towards Petascale In-Package Computing with Unconventional Technologies and Architectures

Abstract

Growing performance and energy efficiency demands of AI workloads put tremendous pressure on today’s computing systems, which is breaking down the two longstanding technological pillars of computing evolution: Moore’s law and von Neuman computer architecture. This has jeopardized the continuous evolution of computing systems. Our research focuses on avoiding this undesired outcome. This talk will showcase how we strive to design fundamentally high-speed and energy-efficient in-package computing systems by employing the principles of heterogeneity, parallelism, and reconfigurability, to contribute innovative solutions that are based on unconventional, but strong, technological pillars such as Integrated Electro-Photonics, 3D Integration, Processing-in-Memory, and Stochastic Computing.

Biography

Dr. Ishan Thakkar is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Kentucky, Lexington, KY. He received his Ph.D. and M.S. in Electrical Engineering from Colorado State University (CSU), Fort Collins, CO in 2018 and 2013, respectively. Dr. Thakkar is the recipient of the outstanding reviewer award from IEEE/ACM CODES+ISSS 2022. He is the recipient of the Best Paper Award from ACM GLSVLSI 2021, a Best Paper Award Nomination from IEEE ISVLSI 2021, the Best Paper Award Honorary Selection from ACM GLSVLSI 2020, the Best Paper Award from the IEEE/ACM SLIP 2016 workshop, a Best Paper Nomination from IEEE ISQED 2016, and a Best Paper Finalist Selection from the IEEE TMSCS journal in 2015, for his research contributions. He is currently an Associate Editor for the IEEE TCVLSI Newsletter. He serves in the ACM SIGDA Executive Team as the Social Media Chair. His research broadly focuses on the design and optimization of unconventional (more-than-Moore) architectures and technologies for energy-efficient, reliable, and secure computing. More specific more-than-Moore technology interests of his include silicon photonics, optical computing, in-memory computing, stochastic/unary computing, monolithic 3D (M3D) integration, and polymer and transparent conductive oxides-based photonic devices and sensors.