Presentation Information
[ME1-2]ALoRA: Hardware-Aware Fine Tuning for Photonic Large Neural Networks
○Taichi Taniguchi1, Mitsumasa Nakajima2, Kohei Ikeda3, Toshikazu Hashimoto2, Satoshi Kawakami1 (1.Kyushu University, 2.NTT Device Technology Laboratories, 3.NTT Basic Research Laboratories)
Keywords:
Highly parallelized scalable photonic computing architectures and devices,Deep learning for photonic device and applications,Optical transformer
We investigated the impact of analog errors on large-scale photonic neural network using an experimentally obtained error model. Performance degradation due to analog error can be recovered by proposed hardware-aware fine-tuning with ~1.6 % trainable parameters.