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Photonic Matrix Computing: From Fundamentals to Applications
In emerging artificial intelligence applications, massive matrix operations require high computing speed and energy efficiency. Optical computing can realize high-speed parallel information processing with ultra-low energy consumption on photonic integrated platforms or in free space, which can well...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8308143/ https://www.ncbi.nlm.nih.gov/pubmed/34206814 http://dx.doi.org/10.3390/nano11071683 |
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author | Cheng, Junwei Zhou, Hailong Dong, Jianji |
author_facet | Cheng, Junwei Zhou, Hailong Dong, Jianji |
author_sort | Cheng, Junwei |
collection | PubMed |
description | In emerging artificial intelligence applications, massive matrix operations require high computing speed and energy efficiency. Optical computing can realize high-speed parallel information processing with ultra-low energy consumption on photonic integrated platforms or in free space, which can well meet these domain-specific demands. In this review, we firstly introduce the principles of photonic matrix computing implemented by three mainstream schemes, and then review the research progress of optical neural networks (ONNs) based on photonic matrix computing. In addition, we discuss the advantages of optical computing architectures over electronic processors as well as current challenges of optical computing and highlight some promising prospects for the future development. |
format | Online Article Text |
id | pubmed-8308143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83081432021-07-25 Photonic Matrix Computing: From Fundamentals to Applications Cheng, Junwei Zhou, Hailong Dong, Jianji Nanomaterials (Basel) Review In emerging artificial intelligence applications, massive matrix operations require high computing speed and energy efficiency. Optical computing can realize high-speed parallel information processing with ultra-low energy consumption on photonic integrated platforms or in free space, which can well meet these domain-specific demands. In this review, we firstly introduce the principles of photonic matrix computing implemented by three mainstream schemes, and then review the research progress of optical neural networks (ONNs) based on photonic matrix computing. In addition, we discuss the advantages of optical computing architectures over electronic processors as well as current challenges of optical computing and highlight some promising prospects for the future development. MDPI 2021-06-26 /pmc/articles/PMC8308143/ /pubmed/34206814 http://dx.doi.org/10.3390/nano11071683 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Cheng, Junwei Zhou, Hailong Dong, Jianji Photonic Matrix Computing: From Fundamentals to Applications |
title | Photonic Matrix Computing: From Fundamentals to Applications |
title_full | Photonic Matrix Computing: From Fundamentals to Applications |
title_fullStr | Photonic Matrix Computing: From Fundamentals to Applications |
title_full_unstemmed | Photonic Matrix Computing: From Fundamentals to Applications |
title_short | Photonic Matrix Computing: From Fundamentals to Applications |
title_sort | photonic matrix computing: from fundamentals to applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8308143/ https://www.ncbi.nlm.nih.gov/pubmed/34206814 http://dx.doi.org/10.3390/nano11071683 |
work_keys_str_mv | AT chengjunwei photonicmatrixcomputingfromfundamentalstoapplications AT zhouhailong photonicmatrixcomputingfromfundamentalstoapplications AT dongjianji photonicmatrixcomputingfromfundamentalstoapplications |