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Approximate Computing: A New Dimension for Hardware Design Tradeoff

Date: 2018-05-17
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Approximate Computing: A New Dimension for Hardware Design Tradeoff

I. Details of the lecture 

Topic: Approximate Computing: A New Dimension for Hardware Design Tradeoff

Time: 10:00-12:00, May 18th, 2018

Location: Room 1-415, FIT Building Tsinghua University

Speaker: Hu Jiang   Professor in the Department of Electrical and Computer Engineering at the Texas A&M University

II. Introduction to the speaker 

Jiang Hu received the B. S. degree in optical engineering from Zhejiang University, China, in 1990, the M. S. degree in physics in 1997, and the Ph. D. degree in electrical engineering from the University of Minnesota in 2001. He was with IBM Microelectronics from January 2001 to June 2002. Currently he is a professor in the Department of Electrical and Computer Engineering at the Texas A&M University. His research interests include VLSI circuit optimization, chip power management, approximate computing and computing acceleration of machine learning. He received a best paper award at the ACM/IEEE Design Automation Conference in 2001, an IBM Invention Achievement Award in 2003 and a best paper award at the IEEE/ACM International Conference on Computer-Aided Design in 2011. He has served as General Chair and Technical Program Chair for the ACM International Symposium on Physical Design, and associated editor for IEEE Transactions on CAD and ACM Transactions on Design Automation of Electronic Systems. He received Humboldt research fellowship in 2012. He is named IEEE Fellow in 2016.

III. Content of lecture 

For a class of applications with growing popularity, such as voice/video/haptic processing and machine learning, occasional and small computing errors are intrinsically tolerable. By deliberately allowing such errors, approximate computing offers either power reduction or performance improvement for hardware designs. This talk will first provide a brief review on recent related works. Then, it will dive into some details on how to build approximate sub-systems using approximate components. Specifically, high level synthesis with consideration of approximation will be introduced. Results on configurable approximate circuit design and approximate JPEG decoder design will also be demonstrated.

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