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Research Highlight: Garrett Rose

[lead]Associate Professor, Electrical Engineering and Computer Science[/lead]

Garrett Rose
Garrett Rose

An EECS research team is helping to develop a computing system that mimics the nervous system to design a chip that would allow computers to operate at an even faster rate and calculate more complicated processing than simple binary-based computing (known as a memristor-based dynamic neural network array, dubbed mrDANNA).

Memristors – a combination of the words memory and resistor – are devices that allow for increasingly faster, more complicated processing than simple binary- based computing. The mrDANNA is a hybrid neuromorphic computing system that mimics the nervous system. It is comprised of both nanoscale memristor devices and more conventional transistor technology integrated on a single silicon chip. This approach allows scientists to take advantage of new technologies that will increase functional density, encourage robust performance and reduce power consumption.

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