Xiaodong Yan advances computer chips with sound waves

Researchers developing neuromorphic computing take inspiration from the brain's synapses to design computer chips. These designs can use dramatically less energy than conventional AI chips. But an emerging field of neuromorphic devices uses sound waves to enable chips to operate faster and more energy-efficiently.

“This could make future neuromorphic hardware more compact, more parallel, and more efficient for tasks that require combining many features, such as pattern recognition, sensory processing and data analysis,” said Xiaodong Yan, Frank L. and Daphna Lederman Professor and MSE assistant professor, in an article with IEEE Spectrum. 

Recently, scientists have developed acoustic devices in which sound waves can encode multiple values in their wave phase. These phase bits, or phi-bits, can in turn support quantum-like logic gates and parallel computing. Whereas conventional bits only symbolize zero or one and require a separate physical component for each bit, phi-bits each represent multiple variables and coexist within one space, said IEEE Spectrum.

“In a topological acoustic synapse, the acoustic wave interactions help transform and organize information before the final readout,” said Yan, who holds a joint appointment in the Department of Electrical and Computer Engineering.