Webinar: Efficient and Reliable Deep Learning at Scale: Hardware and Software

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Speaker:

Dr. Yiran Chen, Duke University

Abstract:

The rapid growth of modern neural network models’ scale generates ever-increasing demands for high computing power of Artificial Intelligence (AI) systems. Many specialized computing devices have been also deployed in the AI systems, forming a truly application-driven heterogeneous computing platform. This talk discusses the importance of hardware/software co-design in the development of AI computing systems. We first use resistive memory based Neural Network (NN) accelerators to illustrate the design philosophy of heterogeneous AI computing systems, and then present several hardware-friendly efficient neural network model design techniques. We also extend our discussions to the reliability and robustness of memristor-based AI systems and introduce algorithmic and system solutions to improve the robustness of such systems. A research roadmap of our relevant research is given at the end of the talk.

Speaker Bio:

Dr. Yiran Chen received B.S (1998) and M.S. (2001) from Tsinghua University and Ph.D. (2005) from Purdue University. After five years in industry, he joined University of Pittsburgh in 2010 as Assistant Professor and then was promoted to Associate Professor with tenure in 2014, holding Bicentennial Alumni Faculty Fellow. He is now the Professor of the Department of Electrical and Computer Engineering at Duke University and serving as the director of the NSF AI Institute for Edge Computing Leveraging the Next-generation Networks (Athena) and the NSF Industry–University Cooperative Research Center (IUCRC) for Alternative Sustainable and Intelligent Computing (ASIC), and the co-director of Duke Center for Computational Evolutionary Intelligence (CEI). His group focuses on the research of new memory and storage systems, machine learning and neuromorphic computing, and mobile computing systems. Dr. Chen has published 1 book and about 500 technical publications and has been granted 96 US patents. He has served as the associate editor of a dozen international academic transactions/journals and served on the technical and organization committees of more than 60 international conferences. He is now serving as the Editor-in-Chief of the IEEE Circuits and Systems Magazine. He received eight best paper awards, one best poster award, and fourteen best paper nominations from international conferences and workshops. He received numerous awards for his technical contributions and professional services. He is a Fellow of the ACM and IEEE and now serves as the chair of ACM SIGDA.