KEYNOTE TALK
Photonic Systems-on-Chip for Deep Learning
Associate Professor
Electrical and Computer Engineering Department
Colorado State University, USA
Abstract: Integrated photonics has shown significant progress over the past decade for Datacom applications and chip-scale communication. More recently, with the continuous growth in the complexity and required computing power for advanced deep learning applications, there has been a lot of interest to realize more energy-efficient and faster artificial intelligence (AI) hardware accelerators that use photonics for not only communication but also for storage and computation. This talk will discuss the most recent advances, challenges, and research opportunities in the development of photonic systems-on-chip for accelerating deep learning applications.
Biography: Mahdi Nikdast is an Associate Professor and Endowed Rockwell-Anderson Professor in the Department of Electrical and Computer Engineering at Colorado State University (CSU), Fort Collins, where he is directing the Electronic-PhotoniC System Design (ECSyD) Laboratory. He received his Ph.D. in Electronic and Computer Engineering from The Hong Kong University of Science and Technology (HKUST), Hong Kong, in 2014. From 2014 to 2017, he was a postdoctoral fellow at McGill University and Polytechnique Montreal, Quebec, Canada. His research interests are at the intersection of integrated photonics, emerging technologies, and high-performance computing. Prof. Nikdast and his students have published numerous papers in refereed journals and international conference publications and across different areas of VLSI, EDA, Photonics, Embedded Systems, Systems-on-Chip (SoCs), Artificial Intelligence (AI), and Computer Architecture. He has edited a book on Silicon Photonics for High-Performance Computing and Beyond, published by Taylor and Francis Group in 2022, and another book on Photonic Interconnects for Computing Systems: Understanding and Pushing Design Challenges, published by River Publishers in 2017. Prof. Nikdast currently serves as an Associate Editor for IEEE Transactions on Very Large Scale Integration Systems (IEEE TVLSI), and has served on the TPC of various international conferences, including DAC, OFC, DATE, ICCAD, ESWEEK, NOCS, etc. He is a co-founder of the International Workshop on Optical/Photonic Interconnects for Computing Systems (OPTICS workshop) and the North American Workshop on Silicon Photonics for High-Performance Computing (SPHPC Workshop). Prof. Nikdast and his team were the recipient of various awards, including the Second Best Project Award at the AMD Technical Forum and Exhibition (AMD-TFE 2010, Taiwan), the Best Paper Award at the Asia Communications and Photonics Conference (ACP 2015, Hong Kong), the Best Paper Award at the Design, Automation, and Test in Europe (DATE) Conference (DATE 2016 – Test Track, Dresden), the Best Paper Award Candidate at ACM Great Lake Symposium on VLSI (GLSVLSI 2018, USA), and the Best Paper Honorable Mention Award at ACM Great Lake Symposium on VLSI (GLSVLSI 2020, China). Prof. Nikdast received the prestigious NSF CAREER Award (2021), the George T. Abell Award for Outstanding Early-Career Faculty (2022), the Rockwell-Anderson Professorship (2022), and the George T. Abell Award for Teaching and Mentoring (2023). He is a Senior Member of the IEEE.
