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Computer Engineering and Systems Group

Texas A&M University College of Engineering

CESG Seminar: Dr. Bo Yuan

Posted on January 25, 2022 by Vickie Winston

Friday, January 25, 2021
4:10 – 5:00 p.m.
via Zoom (link below)
 
Dr. Bo Yuan
Asst. Professor, Dept. of Electrical & Computer Engineering, Rutgers University

Title: “Algorithm and Hardware Co-Design for Efficient Deep Learning: Sparse and Low-rank Perspective”

Talking Points

  • Algorithm and hardware co-design for structured and unstructured deep neural networks
  • Algorithm and hardware co-design for high-order tensor decomposition-based deep neural networks

Abstract
In the emerging artificial intelligence era, deep neural networks (DNNs), a.k.a. deep learning, have gained unprecedented success in various applications. However, DNNs are usually storage intensive, computation intensive and very energy consuming, thereby posing severe challenges on the future wide deployment in many application scenarios, especially for the resource-constraint low-power IoT application and embedded systems. In this talk, I will introduce the algorithm/hardware co-design works for energy-efficient DNN in my group, from both the sparse and low-rank perspectives. First, I will show the benefit of using structured and unstructured sparsity of DNN for designing low-latency and low-power DNN hardware accelerators. In the second part of my talk, I will present an algorithm/hardware co-design framework that leverages low tensor rankness towards energy-efficient high-accuracy DNN model and accelerators.

Biography
Dr. Bo Yuan is currently the assistant professor in the Department of Electrical and Computer Engineering in Rutgers University. Before that, he was with City University of New York from 2015-2018. Dr. Bo Yuan received his bachelor and master degrees from Nanjing University, China in 2007 and 2010, respectively. He received his PhD degree from University of Minnesota, Twin Cities in 2015. His research interests include algorithm and hardware co-design and implementation for machine learning and signal processing systems, error-resilient low-cost computing techniques for embedded and IoT systems and machine learning for domain-specific applications. He is the recipient of Global Research Competition Finalist Award in Broadcom Corporation. Dr. Yuan serves as technical committee track chair and technical committee member for several IEEE/ACM conferences. He is the associated editor of Springer Journal of Signal Processing System

Zoom Link: https://tamu.zoom.us/j/96343481647; Zoom ID: 963 4348 1647

Filed Under: Front Page, Seminars

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