Memristive crossbar arrays perform multiply–accumulate operations by utilizing physical laws, boosting power efficiency and computing throughput. Based on ionic motion, memristive devices are also bio-realistic emulators for artificial neurons and synapses. In this talk, I will first introduce a computing memristor for analog in-memory computing. I will then showcase an AI accelerator made by integrating memristive crossbars with CMOS circuitry. Finally, I will discuss a diffusive memristor and its application in neuromorphic engineering.
Memristive Crossbar Arrays for Analog In-Memory Computing and Neuromorphic Engineering
MTL Seminar Series
Qiangfei Xia (UMass Amherst)
Abstract
Bio
Dr. Xia directs the Nanodevices and Integrated Systems Lab (http://nano.ecs.umass.edu) at UMass Amherst. His research interests include beyond-CMOS devices, integrated systems, and enabling technologies, with applications in machine intelligence, reconfigurable RF systems, and hardware security. He is a ‘highly cited researcher’ (Clarivate) and an IEEE Fellow.