Abstract:

The aggressive scaling of CMOS technology results in large-scale process variations and makes it continually more challenging to create reliable and robust IC design. In this talk, a new technique, referred to as virtual probe (VP), will be presented to efficiently measure, characterize and monitor spatially-correlated variations for nanoscale manufacturing process. VP exploits recent breakthroughs in compressed sensing to accurately predict spatial variations from an exceptionally small set of measurement data. During this presentation, the background on compressed sensing, including its problem formulation and numerical solvers, will be briefly reviewed. Next, the VP methodology and several application examples will be presented. Our experimental results based on industrial measurement data demonstrate the superior performance of VP over other state-of-the-art techniques.

Bio:

Xin Li received the Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA in 2005, and the M.S. and B.S. degrees in Electronics Engineering from Fudan University, Shanghai, China in 2001 and 1998, respectively.
He is currently an Associate Professor in the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA. In 2005, he co-founded Xigmix Inc. to commercialize his PhD research, and served as the Chief Technical Officer until the company was acquired by Extreme DA in 2007. In 2011, Extreme DA was further acquired by Synopsis (Nasdaq: SNPS). From 2009 to 2012, he was the Assistant Director for FCRP Focus Research Center for Circuit & System Solutions (C2S2), a national consortium of 13 research universities (CMU, MIT, Stanford, Berkeley, UIUC, UMich, Columbia, UCLA, among others) chartered by the U.S. semiconductor industry and U.S. Department of Defense to work on next-generation integrated circuit design challenges. His research interests include integrated circuit and signal processing.

Dr. Xin Li has been an Associate Editor of IEEE Trans. on Computer-Aided Design of Integrated Circuits and Systems (TCAD) since 2012 and an Associate Editor of Journal of Low Power Electronics (JOLPE) since 2011. He served on the ACM/SIGDA Outstanding PhD Dissertation Award Selection Committee in 2013, the Technical Program Committee of Design Automation Conference (DAC) from 2011 to 2013, the Technical Program Committee of International Conference on Computer-Aided Design (ICCAD) from 2008 to 2011, the Technical Program Committee of International Workshop on Timing Issues in the Specification and Synthesis of Digital Systems (TAU) from 2010 to 2012, the Technical Program Committee of International Conference on VLSI Design (VLSI) in 2009, and the IEEE Outstanding Young Author Award Selection Committee in 2006. He received the NSF Faculty Early Career Development Award (CAREER) in 2012, the IEEE Donald O. Pederson Best Paper Award in 2013, a Best Paper Award from Design Automation Conference (DAC) in 2010, and two IEEE/ACM William J. McCalla ICCAD Best Paper Awards in 2004 and 2011.