An all memristor chip, built by researchers at the University of California, Santa Barbara, and Stony Brook University, processes data not with digital logic circuits but with elements that mimic, in simplified form, the neurons and synapses of biological brains. When a network like that is exposed to new data, it "learns" as the synapses that connect neurons adjust the neurons' influence on one another.
Robert Legenstein, an associate professor at Graz University of Technology in Austria, wrote: "If this design can be scaled up to large network sizes, it will affect the future of computing … Laptops, mobile phones and robots could include ultra-low-power neuromorphic chips that process visual, auditory and other types of sensory information.
Brain-inspired—or "neuromorphic"—chips have been made before, and IBM is trying to commercialize them. They generally use the same silicon transistors and digital circuits that make up ordinary computer processors. But those digital components are not suited to mimicking synapses, says Dmitri Strukov, an assistant professor at the University of California, Santa Barbara, who led work on the new memristor chip. Many transistors and digital circuits are needed to represent a single synapse. By contrast, each of the 100 or so synapses on the UCSB chip is represented using only a single memristor.
"A [biological] synapse is an analog memory device, and there is really no good way of implementing that in a compact, energy-efficient way with conventional technology," says Strukov. "Memristors by themselves are an analog memory device; it's a perfect match."
The UCSB group's simple chip is just a proof of concept, but the researchers believe their techniques can be scaled up to make larger, more powerful devices. Strukov says the technology could get a helping hand from the efforts companies such as HP and SK Hynix are making to commercialize memristors for data storage.
HP should be able to scale memristor chips to billions and even trillions.
This circuit can learn to recognize simple black-and-white patterns, thanks to devices called memristors located at each place the wires cross.
Nature - Training and operation of an integrated neuromorphic network based on metal-oxide memristors
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