A case study on the performance metrics of integrated photonic computing

Photonic processors use optical signals for computation, leveraging the high bandwidth and low loss of optical links. While many approaches have been proposed, including in-memory photonic circuits, most efforts have focused on the physical design of photonic components rather than full architectural integration with electronic peripheral circuitry. In this study, we present a microarchitecture-level study that estimates the compute efficiency and density of three prominent photonic computing architectures. Our evaluation accounts for both the photonic circuits and the essential peripheral electronics required for opto-electronic and analog–digital conversions. We further demonstrate a heterogeneous photonic–electronic in-memory processing approach for low-latency neural network inference. These results provide a better understanding of the design aspects of photonic computing.