Photonic hardware implementation of spiking neural networks,regarded as a viable potential paradigm for ultra-high speed and energy efficiency computing,leverages spatiotemporal spike encoding and event-driven dynamic...Photonic hardware implementation of spiking neural networks,regarded as a viable potential paradigm for ultra-high speed and energy efficiency computing,leverages spatiotemporal spike encoding and event-driven dynamics to simulate brain-like parallel information processing.Silicon-based microring resonators(MRRs)offer a power efficiency and ultrahigh flexibility scheme to mimic biological neuron,however,their substantial potential for integrated neuromorphic systems remains limited by insufficient exploration of MRR-based spiking digital and analog computation.Here,an all-optical neural dynamics framework,encompassing both excitatory and inhibitory behaviors based on multi-wavelength auxiliary and competition mechanism in an MRR,is proposed numerically.Leveraging multi-wavelength resonance characteristics and wavelength division multiplexing(WDM)technology,a single MRR implements the five fundamental optical digital logic gates:AND,OR,NOT,XNOR and XOR.Besides,the cascading capabilities of MRR-based spiking neurons are demonstrated through multi-level digital logic gates including NAND,NOR,4-input AND,8-input AND,and a full adder,emphasizing their promise for large-scale digital logic networks.Furthermore,an exemplary binary convolution has been achieved by utilizing the proposed MRR-based digital logic operation,illustrating the potential of all-optical binary convolution to compute image gradient magnitudes for edge detection.Such passive photonic neurons and networks promise access to the high transmission speed and low power consumption inherent to optical systems,thus enabling direct hardware-algorithm co-computation and accelerating artificial intelligence.展开更多
基金supports from National Natural Science Foundation of China(62171087,62475036).
文摘Photonic hardware implementation of spiking neural networks,regarded as a viable potential paradigm for ultra-high speed and energy efficiency computing,leverages spatiotemporal spike encoding and event-driven dynamics to simulate brain-like parallel information processing.Silicon-based microring resonators(MRRs)offer a power efficiency and ultrahigh flexibility scheme to mimic biological neuron,however,their substantial potential for integrated neuromorphic systems remains limited by insufficient exploration of MRR-based spiking digital and analog computation.Here,an all-optical neural dynamics framework,encompassing both excitatory and inhibitory behaviors based on multi-wavelength auxiliary and competition mechanism in an MRR,is proposed numerically.Leveraging multi-wavelength resonance characteristics and wavelength division multiplexing(WDM)technology,a single MRR implements the five fundamental optical digital logic gates:AND,OR,NOT,XNOR and XOR.Besides,the cascading capabilities of MRR-based spiking neurons are demonstrated through multi-level digital logic gates including NAND,NOR,4-input AND,8-input AND,and a full adder,emphasizing their promise for large-scale digital logic networks.Furthermore,an exemplary binary convolution has been achieved by utilizing the proposed MRR-based digital logic operation,illustrating the potential of all-optical binary convolution to compute image gradient magnitudes for edge detection.Such passive photonic neurons and networks promise access to the high transmission speed and low power consumption inherent to optical systems,thus enabling direct hardware-algorithm co-computation and accelerating artificial intelligence.
