Optical coherent dot-product chip for sophisticated deep learning regression
Optical coherent dot-product chip for sophisticated deep learning regression
About this item
Full title
Author / Creator
Xu, Shaofu , Wang, Jing , Shu, Haowen , Zhang, Zhike , Sicheng Yi , Bowen, Bai , Wang, Xingjun , Liu, Jianguo and Zou, Weiwen
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
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Scope and Contents
Contents
Optical implementations of neural networks (ONNs) herald the next-generation high-speed and energy-efficient deep learning computing by harnessing the technical advantages of large bandwidth and high parallelism of optics. However, due to the problems of incomplete numerical domain, limited hardware scale, or inadequate numerical accuracy, the majo...
Alternative Titles
Full title
Optical coherent dot-product chip for sophisticated deep learning regression
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2533067155
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2533067155
Other Identifiers
E-ISSN
2331-8422
DOI
10.48550/arxiv.2105.12122
