Name
Title | ||
|---|---|---|
FLOPS: EFficient On-Chip Learning for OPtical Neural Networks Through Stochastic Zeroth-Order Optimization |
Abstract | ||
|---|---|---|
Optical neural networks (ONNs) have attracted extensive attention due to its ultra-high execution speed and low energy consumption. The traditional software-based ONN training, however, suffers the problems of expensive hardware mapping and inaccurate variation modeling while the current on-chip training methods fail to leverage the self-learning capability of ONNs due to algorithmic inefficiency and poor variation- robustness. In this work, we propose an on-chip learning method to resolve the aforementioned problems that impede ONNs' full potential for ultra-fast forward acceleration. We directly optimize optical components using stochastic zeroth-order optimization on-chip, avoiding the traditional high-overhead back-propagation, matrix decomposition, or in situ devicelevel intensity measurements. Experimental results demonstrate that the proposed on-chip learning framework provides an efficient solution to train integrated ONNs with 3~4× fewer ONN forward, higher inference accuracy, and better variation-robustness than previous works. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/DAC18072.2020.9218593 | 2020 57th ACM/IEEE Design Automation Conference (DAC) |
DocType | ISSN | ISBN |
Conference | 0738-100X | 978-1-7281-1085-1 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiaqi Gu | 1 | 18 | 6.97 |
| Zheng Zhao | 2 | 88 | 13.14 |
| Chenghao Feng | 3 | 5 | 3.96 |
| Wuxi Li | 4 | 36 | 6.03 |
| T. Chen | 5 | 49 | 10.96 |
| David Z. Pan | 6 | 2653 | 237.64 |