| 日時(Date) | 平成30年12月4日（火）3限（13:30--15:00) Tue. Dec. 4th, 2018, 3rd Period (13:30--15:00) |
|---|---|
| 場所(Location) | L1 |
| 司会(Chair) | 井上 美智子 教授 |
| 講演者(Presenter) | Krishnendu Chakrabarty (William H. Younger Distinguished Professor, Duke University) |
| 題目(Title) | Design of Fault-Tolerant Neuromorphic Computing Systems |
| 概要(Abstract) | The performance of today’s computing infrastructure is limited by the energy consumption involved in processing, storing, and moving data. In addition, the exponential increase in the volume of data that must be handled by our computational infrastructure is driven in large part by machine-learning applications such as deep neural networks. Conventional computing architectures are unable to deal efficiently with this data volume or with the requirement to transform data into actionable information. Moreover, a major showstopper towards energy efficient computing is the high error rate associated with traditional techniques. There is a need to incorporate fault tolerance in emerging computing architectures and circuit designs. This talk will first introduce the audience to the exciting and emerging area of brain-inspired neuromorphic computing systems for machine-learning hardware. First, the presenter will describe RRAM-based crossbars and their role in neuromorphic computing systems. Following this, the need for testing and fault tolerance will be motivated in light of imperfect fabrication technologies, as well as technology limitations such as write endurance in RRAM cells. The speaker will present a physics-based classification and analysis of memristor fault origins. These faults origins will be systematically attributed to process variations and manufacturing defects. This study of memristor fault origins and the resulting conclusions provides valuable feedback for the fabrication and the design of memristor-based circuits and systems. Fault models and test solutions will be presented. Subsequently, techniques for online testing and fault-tolerant training will be described. Finally, time permitting, the speaker will describe an efficient fault tolerance method inspired by algorithm-based fault tolerance (ABFT), and referred to as extended-ABFT (X-ABFT), for fault detection and error correction. |
| 講演言語(Language) | English |
| 講演者紹介(Introduction of Lecturer) | Krishnendu Chakrabarty received the B. Tech. degree from the Indian Institute of Technology, Kharagpur, in 1990, and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1992 and 1995, respectively. He is now the William H. Younger Distinguished Professor and Department Chair of Electrical and Computer Engineering, and Professor of Computer Science, at Duke University. Prof. Chakrabarty is a recipient of the National Science Foundation CAREER award, the Office of Naval Research Young Investigator award, the Humboldt Research Award from the Alexander von Humboldt Foundation, Germany, the IEEE Transactions on CAD Donald O. Pederson Best Paper Award (2015), the ACM Transactions on Design Automation of Electronic Systems Best Paper Award (2017), and over a dozen best paper awards at major conferences. He is also a recipient of the IEEE Computer Society Technical Achievement Award (2015), the IEEE Circuits and Systems Society Charles A. Desoer Technical Achievement Award (2017), the Semiconductor Research Corporation Technical Excellence Award (2018), the IEEE Test Technology Technical Council Bob Madge Innovation Award (2018), and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur (2014). He is a Research Ambassador of the University of Bremen (Germany) and a Hans Fischer Senior Fellow at the Institute for Advanced Study, Technical University of Munich, Germany. He is a 2018 recipient of the Japan Society for the Promotion of Science (JSPS) Fellowship in the “Short Term S: Nobel Prize Level” category, and he was a 2009 Invitational Fellow of JSPS. Prof. Chakrabarty is a recipient of multiple IBM Faculty Awards and HP Labs Open Innovation Research Awards. Prof. Chakrabarty’s current research projects include: testing and design-for-testability of integrated circuits and systems; microfluidic biochips; hardware security; machine learning for fault diagnosis and failure prediction; neuromorphic computing systems. He has served as a Distinguished Visitor of the IEEE Computer Society (2005-2007, 2010-2012), a Distinguished Lecturer of the IEEE Circuits and Systems Society (2006-2007, 2012-2013), and an ACM Distinguished Speaker (2008-2016). Prof. Chakrabarty served as the Editor-in-Chief of IEEE Design & Test of Computers during 2010-2012 and ACM Journal on Emerging Technologies in Computing Systems during 2010-2015. Currently he serves as the Editor-in-Chief of IEEE Transactions on VLSI Systems. |