With Moore’s law and Dennard scaling now being limited by fundamental physics, the trend in processor heterogeneity suggests the possibility for special-purpose photonic processors such as neural networks or RF-signal & image filtering. Here unique opportunities exist, for example, given by algorithmic parallelism of analog and distributed non-van Neuman architectures enabling non-iterative O(1) processors with ps-short delay towards real-time decision making. Here, I will share our latest work on photonic information processors to include a photonic tensor core including multistate photonic nonvolatile random-access memory [Appl. Phys. Rev.], and a massively parallel Fourier-optics convolutional processor [Optica]. In summary, photonics connects the worlds of electronics and optics, thus enabling new concepts of efficient intelligence information processing via algorithm-hardware homomorphism empowered by the distinctive properties of light.
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