Freely scalable and reconfigurable optical hardware for deep learning
Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic processors are impeded by the costs of communicatio...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-02-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-82543-3 |