RADICAL: Reconfiguration-Aware Direct-Connect AI Cluster using Spatial-and-Wavelength Selective Switching

Abstract

We present RADICAL, the silicon-photonic-enabled Reconfiguration-Aware Direct-Connect AI Cluster that integrates a custom spatial-and-wavelength selective switch (SWSS) with the Linux network stack. RADICAL deploys a packaged 4x4x4$\lambda$ microring-based SWSS into a four-GPU-server cluster using standard SFP28 optical transceivers, and a reconfiguration-aware host-networking interface to demonstrate a direct-connect reconfigurable optical fabric. The SWSS provides dynamic spatial and wavelength routing with 3.2-6.8 dB path loss, average wavelength and spatial crosstalk isolation exceeding 25 dB, and error-free 25 Gbps signal recovery across routing paths. At the system level, RADICAL validates reconfiguration-aware operation through continuous bulk data transfers totaling 6.4 TBytes over 10 minutes. We further demonstrate multitenant AI training across reconfigurable link topologies, including four ResNet-18 instances and six nanoGPT instances, with the latter sustained for more than five hours.

arXiv comment14 pages, 16 figures, Accepted for publication in the Journal of Optical Communications and Networking (JOCN), Oct. 2026