Associate Professor, School of Electrical and Computer Engineering, Georgia Institute of Technology
Title: Ferroelectric Devices, Circuits and Architectures for AI Hardware Design
Abstract: In this presentation, I will present the recent progresses on doped HfO2 based ferroelectric devices such as FeFET. First, I will discuss the fundamental device physics including the minor loop switching and history effect, the drain-erase scheme and the variability and scalability of FeFET. Machine learning assisted predictive modeling framework for phase variation is proposed. Second, I will present compute-in-memory (CIM) paradigm for deep neural network acceleration. A prototype CIM inference chip design using 28 nm FeFET is showcased. A new concept on ferroelectric non-volatile capacitor for charge-domain computing is proposed, and the related capacitive crossbar array is experimentally demonstrated. Hybrid synapse that combines charging/discharging mechanism and non-volatile storage is proposed for in-situ training. Finally, 3D NAND architecture based on FeFET is proposed for implementing ultra-large scale AI model.
Shimeng Yu is currently an associate professor of electrical and computer engineering at Georgia Institute of Technology. He received the B.S. degree in microelectronics from Peking University in 2009, and the M.S. degree and Ph.D. degree in electrical engineering from Stanford University in 2011 and 2013, respectively. From 2013 to 2018, he was an assistant professor at Arizona State University.
Prof. Yu’s general research interests are the semiconductor devices and integrated circuits for energy-efficient computing systems. His expertise is on the emerging non-volatile memories for applications such as deep learning accelerator, in-memory computing, and 3D integration. Among Prof. Yu’s honors, he was a recipient of NSF Faculty Early CAREER Award in 2016, IEEE Electron Devices Society (EDS) Early Career Award in 2017, ACM Special Interests Group on Design Automation (SIGDA) Outstanding New Faculty Award in 2018, Semiconductor Research Corporation (SRC) Young Faculty Award in 2019, IEEE Circuits and Systems Society (CASS) Distinguished Lecturer in 2021, and IEEE Electron Devices Society (EDS) Distinguished Lecturer in 2022, etc.
Prof. Yu’s 400 journal/conference publications received more than 22,000 citations (Google Scholar) with H-index 72. He is the theme leads of two SRC/DARPA JUMP 2.0 centers on intelligent memory/storage and heterogeneous/monolithic 3D integration with combined funding level >$90M.
Prof. Yu has served many premier conferences as technical program committee, including IEEE International Electron Devices Meeting (IEDM), IEEE Symposium on VLSI Technology and Circuits, IEEE International Reliability Physics Symposium (IRPS), ACM/IEEE Design Automation Conference (DAC), ACM/IEEE Design, Automation & Test in Europe (DATE), ACM/IEEE International Conference on Computer-Aided-Design (ICCAD), etc. He serves an editor for IEEE Electron Device Letters (EDL). He is a senior member of the IEEE.
Host: Dr. Kyusang Lee
Organizer: Dr. Mona Zebarjadi