Software-Reconfigurable Optical Routing Architecture for Adaptive AI Computation

Abstract

This invention relates to an artificial intelligence (AI) processor architecture that employs software-reconfigurable optical pathways for internal data routing. Unlike conventional chips with fixed electrical or photonic interconnects, this design enables dynamic light-based routing controlled by software to optimize data movement across cores, accelerators, and memory. A photonic mesh composed of tunable waveguides and optical switches is managed by a reconfiguration algorithm in the chip's control plane. Path topology adapts based on workload type or phase (e.g., training vs. inference) to reduce latency, congestion, and energy use through photonic parallelism. Switching elements include phase-change materials, optical MEMS, or electro-optic modulators. Routing maps are defined in real time via software APIs, supporting neural architecture switching and mixed AI workloads. This hybrid architecture delivers real-time self-optimization, adaptive bandwidth control, and energy-efficient parallel computation, suited for datacenters, edge AI, and autonomous platforms.

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