Memristor, also known as a resistance switch, is an electronic device whose internal states are dependent on the history of the current and/or voltage it has experienced. With their working mechanisms based on ion migration, the switching dynamics and electrical behavior of memristive devices highly resemble those of synapses and neurons. This has made memristors a promising candidate for brain-inspired computing with significant advantages in speed-energy efficiency. Built into large-scale crossbar arrays to form neural networks, memristive devices perform in-memory computing with a massive parallelism by utilizing physical laws (such as Ohm’s law for multiplication and Kirchhoff current law for accumulation). Their ability to directly interface with analog signals from sensors without analog/digital conversions could further reduce the processing time and energy overhead.
I will first talk about the development of high performance HfO2 and SiO2 memristors, crossbar arrays with 2 nm feature size, and three-dimensional circuits with eight crossbar layers. I will then showcase the integration of large memristor crossbar arrays for analog signal and image processing, and the implementation of multilayer memristor neural networks for machine learning applications including pattern recognition, time series regression and human gait classification. Finally, I will briefly introduce a diffusive memristor as a bio-realistic synapse and neuron emulator, an all-memristor based neural network, and other applications of memristors in reconfigurable radiofrequency systems and hardware security.
Dr. Xia is a professor of Electrical & Computer Engineering at UMass Amherst and head of the Nanodevices and Integrated Systems Lab (http://nano.ecs.umass.edu). Before joining UMass, he spent three years at Hewlett-Packard Laboratories. He received his Ph.D. in Electrical Engineering in 2007 from Princeton University. Dr. Xia's research interests include beyond-CMOS devices, integrated systems and enabling technologies, with applications in machine intelligence, reconfigurable RF system and hardware security. He is a recipient of DARPA Young Faculty Award, NSF CAREER Award, and the Barbara H. and Joseph I. Goldstein Outstanding Junior Faculty Award. Dr. Xia is a senior member of IEEE and a senior member of SPIE.