The recent artificial intelligence (AI) boom has been largely driven by three confluence forces: algorithms, data, and computing power enabled by modern integrated circuits (ICs) including specialized AI accelerators. This talk will present a closed-loop perspective for synergistic AI and agile IC design with two main themes, AI for IC and IC for AI. As the semiconductor technology enters the era of extreme scaling, IC design and manufacturing complexities become extremely high. More intelligent and agile IC design technologies are needed than ever to optimize performance, power, manufacturability, design cost, etc., and to deliver equivalent scaling to Moore’s Law. I will present some recent results leveraging modern AI and machine learning advancement with domain-specific customizations for agile IC design and manufacturing closure. Meanwhile, customized ICs, including those with beyond-CMOS technologies can drastically improve AI performance and energy efficiency by orders of magnitude. I will present some recent results on hardware/software co-design for high performance and energy-efficient optical neural networks. The bidirectional feedback of synergistic AI and IC design holds great potential to significantly advance the state-of-the-art of each other.

Speaker Bio:

Prof. David Z. Pan is currently Silicon Labs Endowed Chair Professor at the Department of Electrical and Computer Engineering, The University of Texas at Austin. His research interests include bidirectional AI and IC interactions, electronic design automation, design for manufacturing, hardware security, and CAD for analog/mixed-signal ICs and emerging technologies. He has published over 380 refereed journal/conference papers and 8 US patents. He has served in many journal editorial boards and conference committees, including various leadership roles such as ICCAD 2019 General Chair, ASP-DAC 2017 TPC Chair, and ISPD 2008 General Chair. He has received many awards, including SRC Technical Excellence Award, 19 Best Paper Awards (ISPD 2020, ASP-DAC 2020, DAC 2019, GLSVLSI 2018, VLSI Integration 2018, HOST 2017, SPIE 2016, ISPD 2014, ICCAD 2013, ASP-DAC 2012, ISPD 2011, IBM Research 2010 Pat Goldberg Memorial Best Paper Award in CS/EE/Math, ASP-DAC 2010, DATE 2009, ICICDT 2009, SRC Techcon in 1998, 2007, 2012 and 2015), DAC Top 10 Author Award in Fifth Decade, ASP-DAC Frequently Cited Author Award, Communications of ACM Research Highlights, ACM/SIGDA Outstanding New Faculty Award, NSF CAREER Award, IBM Faculty Award (4 times), and many international CAD contest awards. He has graduated 36 PhD students and postdocs who have won many awards, including the First Place of ACM Student Research Competition Grand Finals in 2018, ACM/SIGDA Student Research Competition Gold Medal (twice), ACM Outstanding PhD Dissertation in EDA Award (twice), EDAA Outstanding Dissertation Award (twice), etc. He is a Fellow of IEEE and SPIE.