Emerging Memory Fundamentals
Shan X. Wang, Leland T. Edwards Professor in the School of Engineering, Stanford University
Smaller lithographic features in semiconductor devices has improved the speed of computing, but it has increased power consumption. A possible solution to limit power consumption is normally-off computing in which on-chip volatile memories are replaced with non-volatile memories. In-memory computing based on emerging Phase Change Memory (PCM), Resistive RAM (RRAM), Ferroelectric RAM (FRAM), and Magnetoresistive RAM (MRAM) can overcome the von Neumann bottleneck caused by the standard computer architecture in which the processor and memory are separate and data moves between the two. Therefore, we will discuss the principles and materials underlying these non-volatile memory technologies, providing working knowledge necessary to appreciate and create innovative future computing systems including Internet of Things (IOT), data center applications, and Edge AI.
Dr. Wang is the Leland T. Edwards Professor in the School of Engineering, Stanford University. He is a Professor and Associate Chair of Materials Science & Engineering and jointly a Professor of Electrical Engineering, and by courtesy, a Professor of Radiology (Stanford School of Medicine). He directs the Center for Magnetic Nanotechnology and is a leading expert in biosensors, information storage and spintronics. His research and inventions span across a variety of areas including magnetic biochips, in vitro diagnostics, cancer biomarkers, magnetic nanoparticles, magnetic sensors, magnetoresistive random access memory, and magnetic integrated inductors.
He has over 290 publications, and holds 63 issued or pending patents in these and interdisciplinary areas. He was named an inaugural Fred Terman Fellow, and was elected a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a Fellow of American Physical Society (APS) for his seminal contributions to magnetic materials and nanosensors. His team won the Grand Challenge Exploration Award from Gates Foundation (2010), the XCHALLENGE Distinguished Award (2014), and the Bold Epic Innovator Award from the XPRIZE Foundation (2017).
Dr. Wang cofounded three high-tech startups in Silicon Valley, including MagArray, Inc. and Flux Biosciences, Inc. In 2018 MagArray launched a first of its kind lung cancer early diagnostic assay based on LASSO logistic regression or support vector machine (SVM). Through his participation in the Center for Cancer Nanotechnology Excellence (as co-PI of the CCNE), the Joint University Microelectronics Program (JUMP), and the Energy Efficient Electronic Science (E3S) Center, he is actively engaged in the application of artificial intelligence (AI) for biomedicine, and is developing emerging memories for energy efficient computing and AI hardware.
Dr. Wang obtained his PhD in Electrical and Computer Engineering from Carnegie Mellon University in 1993, MS in Physics from Iowa State University in 1988, and BS in Physics from the University of Science and Technology of China in 1986.