RRAM technology has made significant progresses in the past few years as a competitive candidate for the next generation non-volatile memory (NVM). In this talk, I will introduce RRAM’s new applications beyond NVM for neuro-inspired computing and hardware security. Firstly, I will show an experimental demonstration of RRAM synaptic weights for offline and online training of neural network. Secondly, I will present a simulation study of the non-ideal device effects (e.g. limited precision and variations) on the system-level learning accuracy of MNIST handwritten digits using spare coding algorithm. Furthermore, I will discuss the challenges of scaling up the synaptic crossbar array from the circuit and architecture perspective. Lastly, I will introduce how to leverage the RRAM variability as physical unclonable function (PUF) for device authentication and cryptographic key generation.
Shimeng Yu received the B.S. degree in microelectronics from Peking University, Beijing, China in 2009, and the M.S. degree and Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, USA in 2011, and in 2013, respectively. He is currently an assistant professor of electrical engineering and computer engineering at Arizona State University, Tempe, AZ, USA.
His research interests are emerging nano-devices and circuits with a focus on the resistive memories for different applications including monolithic 3D integration, brain-inspired neuromorphic computing, hardware security, radiation-hard electronics, etc. He has published >50 journal papers and >90 conference papers with citations >3000 and H-index 26.
Among this honors, he is a recipient of the Stanford Graduate Fellowship from 2009 to 2012, the IEEE Electron Devices Society Masters Student Fellowship in 2010, the IEEE Electron Devices Society PhD Student Fellowship in 2012, the DOD-DTRA Young Investigator Award in 2015, and the NSF CAREER Award in 2016.
He did summer internship in IMEC, Belgium in 2011, and IBM TJ Watson Research Center in 2012. He held visiting faculty position in Tsinghua University in 2016, and Air Force Research Laboratory in 2016. He has been serving the Technical Committee of Nanoelectronics and Gigascale Systems, IEEE Circuits and Systems Society since 2014.