![](http://mpsoc-forum.org/archive/2024/wp-content/uploads/2023/01/Sudeep-Pasricha.jpg)
Sudeep Pasricha
Colorado State University, USA
Processing in Memory for AI Acceleration with Silicon Photonics
Abstract
The massive data deluge from mobile, IoT, and edge devices, together with powerful innovations in data science and hardware processing, have established AI and machine learning as the cornerstones of modern medical, automotive, industrial automation, and consumer electronics domains. Domain-specific AI accelerators now dominate CPUs and GPUs for energy-efficient AI processing. However, the evolution of these electronic accelerators is facing fundamental limits due to the slowdown of Moore’s law and the reliance on metal wires. Further, data movement remains one of the biggest energy and performance bottlenecks in current state-of-the-art AI accelerators. In this talk, I will present my vision of how the paradigms of in-memory computing and silicon photonics can be combined to drive an entirely new class of AI hardware accelerators that can provide orders of magnitude energy and performance improvements over today’s accelerators.
Biography
Sudeep Pasricha is a Professor in the Department of Electrical and Computer Engineering at Colorado State University (CSU), Fort Collins where he is the Director of the Embedded, High Performance, and Intelligent Computing (EPIC) Laboratory. He is a former University Distinguished Monfort Professor and College of Engineering Rockwell-Anderson Professor. Prior to joining CSU, he has several years of industry experience working as a design engineer in STMicroelectronics and Conexant. He received his Ph.D. in Computer Science from the University of California, Irvine in 2008. His research broadly focuses on software algorithms, hardware architectures, and hardware-software co-design for energy-efficient, fault-tolerant, real-time, and secure computing, for embedded, IoT, and cyber-physical systems. Prof. Pasricha has published over 300 papers in peer-reviewed journals and conferences that have received 17 best paper awards and finalist selections. He has also co-authored seven books and multiple patents. His contributions have been recognized with several awards, including the IEEE Computer Society TCVLSI Research Achievement Award, IEEE Computer Society TCSC Award for Research Excellence, AFOSR Young Investigator Award, ACM Technical Leadership Award, and ACM SIGDA Distinguished Service Award. He is currently the Vice Chair of ACM SIGDA. He is a Senior Associate Editor for the ACM Journal of Emerging Technologies in Computing, and an Associate Editor with several ACM and IEEE journals. He is an IEEE Fellow, AAIA Fellow, an ACM Distinguished Member, and an ACM Distinguished Lecturer.
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