Harnessing Photonics for Machine Intelligence

TL;DR

This review explores how integrated photonics can revolutionize AI acceleration by enabling scalable, efficient, and adaptable computing systems through cross-layer design and automation.

Contribution

It introduces a comprehensive system-level perspective on photonic computing, emphasizing co-design, workload adaptability, and the role of electronic-photonic design automation.

Findings

Photonic computing offers high bandwidth and parallelism for AI workloads.

Cross-layer co-design enhances efficiency and versatility in photonic systems.

Electronic-Photonic Design Automation is crucial for scalable system development.

Abstract

The exponential growth of machine-intelligence workloads is colliding with the power, memory, and interconnect limits of the post-Moore era, motivating compute substrates that scale beyond transistor density alone. Integrated photonics is emerging as a candidate for artificial intelligence (AI) acceleration by exploiting optical bandwidth and parallelism to reshape data movement and computation. This review reframes photonic computing from a circuits-and-systems perspective, moving beyond building-block progress toward cross-layer system analysis and full-stack design automation. We synthesize recent advances through a bottleneck-driven taxonomy that delineates the operating regimes and scaling trends where photonics can deliver end-to-end sustained benefits. A central theme is cross-layer co-design and workload-adaptive programmability to sustain high efficiency and versatility across evolving application domains at scale. We further argue that Electronic-Photonic Design Automation (EPDA) will be pivotal, enabling closed-loop co-optimization across simulation, inverse design, system modeling, and physical implementation. By charting a roadmap from laboratory prototypes to scalable, reproducible electronic-photonic ecosystems, this review aims to guide the CAS community toward an automated, system-centric era of photonic machine intelligence.