Scalable Neuromorphic Hardware Image
Single transistor neurons and synapses fabricated using a standard silicon CMOS process. They are co-integrated on the same 8-inch wafer.

Researchers from Korea Advanced Institute of Science and Technology (KAIST) fabricated brain-inspired highly scalable neuromorphic hardware by co-integrating single transistor neurons and synapses. Using standard silicon CMOS technology, the neuromorphic hardware is expected to reduce chip cost and simplify fabrication procedures.

Neuromorphic hardware has attracted a great deal of attention because of its artificial intelligence functions, consuming ultra-low power by mimicking the human brain. To make neuromorphic hardware work, a neuron that generates a spike when integrating a certain signal, and a synapse remembering the connection between two neurons are necessary, just like the biological brain. However, since neurons and synapses constructed on digital or analog circuits occupy a large space, there is a limit in terms of hardware efficiency and costs. Since the human brain consists of about 1011 neurons and 1014 synapses, it is necessary to improve the hardware cost in order to apply it to mobile and IoT devices.

To solve the problem, the research team mimicked the behavior of biological neurons and synapses with a single transistor and co-integrated them onto an 8-inch wafer. The manufactured neuromorphic transistors have the same structure as the transistors for memory and logic that are currently mass-produced. In addition, the neuromorphic transistors proved for the first time that they can be implemented with a ‘Janus structure’ that functions as both neuron and synapse, just like coins have heads and tails.

Professor Yang-Kyu Choi said that this work can dramatically reduce the hardware cost by replacing the neurons and synapses that were based on complex digital and analog circuits with a single transistor. "By co-integrating single transistor neurons and synapses on the same wafer using a standard CMOS process, the hardware cost of the neuromorphic hardware has been improved, which will accelerate the commercialization of neuromorphic hardware,” said Joon-Kyu Han, the first author.

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