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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...
Autores principales: | Bernstein, Liane, Sludds, Alexander, Hamerly, Ryan, Sze, Vivienne, Emer, Joel, Englund, Dirk |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862662/ https://www.ncbi.nlm.nih.gov/pubmed/33542343 http://dx.doi.org/10.1038/s41598-021-82543-3 |
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