Against conventional architecture, the novel device enables processing to happen within the storage of a system.
The material has enabled researchers to develop a novel synapse device composed of two transistors interconnected through a storage node. According to the team, controlling the node's charging and discharging rate has enabled the AI semiconductor to meet the diverse performance metrics required for high-level performance.
In addition, including such devices in a large-scale AI system requires the output current of synaptic devices to be minimized. The team confirmed the "possibility of utilizing the ultra-thin film insulators inside the transistors to control the current, making them suitable for large-scale AI.
"The significance of my research team's achievement is that we overcame the limitations of conventional AI semiconductor technologies that focused solely on material development," said Professor Yoonyoung Chung, the study's lead author. The team could obtain linear and symmetrical programming characteristics by employing its novel structure for a synaptic device.
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