Highly nonlinear, fast and repeatable threshold switching behaviours of diffusive memristors.
A new type of nanodevice for computer microprocessors that can mimic the functioning of a neural synapse has been developed by Engineers at the University of Massachusetts Amherst. Such neuromorphic computing in which microprocessors are configured more like human brains is one of the most promising transformative computing technologies currently under study. Prof. 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.
Most previous work in memristors has not implemented diffusive dynamics without using large standard technology found in integrated circuits commonly used in microprocessors, microcontrollers, static random access memory and other digital logic circuits.
Schematic illustration of the analogy between Ca2+ and Ag dynamics, and short-term synaptic plasticity of the diffusive memristor.
The researchers say they demonstrated a bio-inspired solution to the diffusive dynamics that is fundamentally different from the standard technology for integrated circuits while sharing great similarities with synapses. They say, “Specifically, we developed a diffusive-type memristor where diffusion of atoms offers a similar dynamics and the needed time-scales as its bio-counterpart, leading to a more faithful emulation of actual synapses, i.e., a true synaptic emulator.”
The researchers say, “The results here provide an encouraging pathway toward synaptic emulation using diffusive memristors for neuromorphic computing.” http://www.umass.edu/newsoffice/article/umass-amherst-engineers-lead-research-team
http://www.nature.com/nmat/journal/vaop/ncurrent/full/nmat4756.html
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