Neuromorphic Computing Based on Wavelength-Division Multiplexing

Optical neural networks (ONNs), or optical neuromorphic hardware accelerators, have the potential to dramatically enhance computing power and energy efficiency of mainstream electronic processors, due their ultralarge bandwidths up 10s terahertz together with analog architecture that avoids need for reading writing data back forth. Different multiplexing techniques been employed demonstrate ONNs, amongst which wavelength division (WDM) make sufficient use unique advantages optics in terms broad bandwidths. Here, we review recent advances WDM based focusing on methods integrated microcombs implement ONNs. We present results human image processing using an convolution accelerator operating at 11 Tera operations per second. The open challenges limitations ONNs be addressed future applications are also discussed.