Qiangfei Xia, Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, Email: qxia@umass.edu

Abstract:

It becomes increasingly difficult to improve the speed-energy efficiency of traditional digital processors because of limitations in transistor scaling and the von Neumann architecture. Computing systems augmented with emerging devices such as resistance switches (also known as memristors) offer an attractive solution. Built into large-scale crossbar arrays, they perform in-memory computing by utilizing physical laws, such as Ohm’s law for multiplication and Kirchhoff’s current law for accumulation. The current readout at all columns is finished simultaneously regardless of the array size, offering massive parallelism in vector-matrix multiplication and hence high computing throughput. The ability to directly interface with analog signals from sensors without analog/digital conversion could further reduce the processing time and energy overhead. In this talk, I will first introduce a high-performance analog resistance switch that meets most requirements for in-memory computing in artificial neural networks. I will then discuss the challenges and solutions in integrating these devices into large-scale arrays. Finally, I will showcase the implementation of multilayer neural networks for machine intelligence applications.

Bio:

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 the 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 systems, and hardware security. He is a recipient of the DARPA Young Faculty Award, NSF CAREER Award, and the Barbara H. and Joseph I. Goldstein Outstanding Junior Faculty Award. He serves on the technical committees of several conferences such as ISCAS, IEDM, EDTM, EIPBN (2023 conference chair).

Admission Fee:

All admissions free. Suggested donations:

Non-IEEE:  $5, Students (non-IEEE): $3, IEEE Members (not members of CASS or SSCS): $3

Date and time

Thursday, February 24th, 2021, 6:00 PM – 7:00 PM PST

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Location

Online event

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