Presentation
Crosstalk-Aware Mapping for Optical Neural Networks
DescriptionBy leveraging wavelength division multiplexing (WDM) technology, optical neural networks (ONNs) built with micro-ring resonator (MRR) arrays have recently emerged as a powerful solution for accelerating the energy-intensive matrix-vector multiplication operations in artificial intelligence applications. Despite their promise, the scalability of MRR-based computing systems is severely limited by adjacent channel crosstalk. This challenge arises from the inherent imperfections in MRR filtering, which lead to signal leakage between neighboring channels. As the number of WDM channels increases, this accumulated adjacent channel interference intensifies, posing a substantial obstacle to large-scale ONNs. In this work, we propose the Crosstalk-Aware Mapping (CAM) strategy that mitigates this crosstalk by optimizing the weight mapping scheme for MRR arrays. This is achieved through array-wise weight reallocation and the optimization of phase-shift combinations on both row and column levels. Extensive experimental results on MRR-ONN systems substantiate the effectiveness of CAM, with average performance improvements of 61.92%, 48.70%, and 63.08% on the MNIST, Fashion-MNIST, and CIFAR-10 datasets.
Event Type
Networking
Work-in-Progress Poster
TimeMonday, June 236:00pm - 7:00pm PDT
LocationLevel 2 Lobby