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Freely scalable and reconfigurable optical hardware for deep learning
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 communication, therma...
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| Pubblicato in: | Sci Rep |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7862662/ https://ncbi.nlm.nih.gov/pubmed/33542343 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-021-82543-3 |
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