FIONA: Fine-grained Incoherent Optical DNN Accelerator Search for Superior Efficiency and Robustness

Incoherent optical DNN accelerators (OAs) are booming thanks to unparalleled performance-per-watt and excellent scalability. To boost their innovative development, a recent work revolutionarily proposed automatic OA search. However, the robustness and the acceleration performance of the generated OAs are below expectation, because the impacts of inter-tile data transfer and fabrication process & thermal variations (i.e., PTVs) on OAs were ignored. Both hinder OA design automation from being a reality. To resolve theses challenges, we develop FIONA, a novel framework for Fine-grained Incoherent Optical DNN Accelerator search towards both superior acceleration efficiency and inference robustness. Compared against 5 state-of-the-art incoherent OAs on 9 DNN benchmarks, extensive experiments and ablation studies validate the effectiveness of FIONA, achieving up to 198.01× acceleration efficiency improvement based on guaranteed robustness.