The pioneering research of Joshua Yang and Qiangfei Xia of the Electrical and Computer Engineering Department is attracting international media attention in Scientific American, Science magazine, and many other outlets after being featured in the scientific journal Nature Materials. Yang and Xia are leading a research team that is developing new types of nanoscale devices for microprocessors that can mimic the functioning of a biological synapse, the junction between two neurons in the human brain. The new devices are also energy efficient.
Among other media outlets, the news has been carried in: Science Daily, MSN, Genetic Engineering & Biotechnology News, Nanotechweb.org, Futurism, IEEE Spectrum, ZMEscience.com, Communications of the ACM [Association for Computing Machinery], Motherboard, Phys.org, Nanowerk, Supercomputing Online News, Engineers Australia, Smart2zero.com, EETimes Europe, HPCwire.com, EETimes, Wirelessdesignmag.com, ExtremeTech.
Such neuromorphic computing—meaning microprocessors configured more like human brains than like traditional computer chips—is one of the most promising transformative computing technologies currently under study. Yang describes the research as part of collaborative work on a new type of memristive device. Memristive devices are electrical resistance switches that can alter their resistance based on the history of applied voltage and current. These devices can store and process information and offer several key performance characteristics that exceed conventional integrated circuit technology.
“Memristors have become a leading candidate to enable neuromorphic computing by reproducing the functions in biological synapses and neurons in a neural network system, while providing advantages in energy and size,” the researchers say.
Xia says, “This work opens a new avenue of neuromorphic computing hardware based on memristors.”
The title of the groundbreaking Nature Materials article is “Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing.”
In addition to Xia and Yang, the authors include Zhongrui Wang, Saumil Joshi, Hao Jiang, Rivu Midya, Peng Lin, of the UMass Amherst Electrical and Computer Engineering Department; Sergey E. Savel’ev of the Department of Physics, Loughborough University in the U.K.; Miao Hu, Ning Ge, John Paul Strachan, Zhiyong Li, and R. Stanley Williams of the Hewlett Packard Labs, Palo Alto, Calif.; Qing Wu and Mark Barnell of the Air Force Research Lab, Information Directorate, Rome, New York; GengLin Li of the UMass Amherst Department of Biology, and Huolin L. Xin of the Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York. (October 2016)