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Magnetic Elements for Neuromorphic Computing
Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann bottleneck. Artificial synapses and neurons can be...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7321415/ https://www.ncbi.nlm.nih.gov/pubmed/32486173 http://dx.doi.org/10.3390/molecules25112550 |
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author | Blachowicz, Tomasz Ehrmann, Andrea |
author_facet | Blachowicz, Tomasz Ehrmann, Andrea |
author_sort | Blachowicz, Tomasz |
collection | PubMed |
description | Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann bottleneck. Artificial synapses and neurons can be implemented into conventional hardware using new software, but also be created by diverse spintronic devices and other elements to completely avoid the disadvantages of recent hardware architecture. Here, we report on diverse approaches to implement neuromorphic functionalities in novel hardware using magnetic elements, published during the last years. Magnetic elements play an important role in neuromorphic computing. While other approaches, such as optical and conductive elements, are also under investigation in many groups, magnetic nanostructures and generally magnetic materials offer large advantages, especially in terms of data storage, but they can also unambiguously be used for data transport, e.g., by propagation of skyrmions or domain walls. This review underlines the possible applications of magnetic materials and nanostructures in neuromorphic systems. |
format | Online Article Text |
id | pubmed-7321415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73214152020-06-29 Magnetic Elements for Neuromorphic Computing Blachowicz, Tomasz Ehrmann, Andrea Molecules Review Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann bottleneck. Artificial synapses and neurons can be implemented into conventional hardware using new software, but also be created by diverse spintronic devices and other elements to completely avoid the disadvantages of recent hardware architecture. Here, we report on diverse approaches to implement neuromorphic functionalities in novel hardware using magnetic elements, published during the last years. Magnetic elements play an important role in neuromorphic computing. While other approaches, such as optical and conductive elements, are also under investigation in many groups, magnetic nanostructures and generally magnetic materials offer large advantages, especially in terms of data storage, but they can also unambiguously be used for data transport, e.g., by propagation of skyrmions or domain walls. This review underlines the possible applications of magnetic materials and nanostructures in neuromorphic systems. MDPI 2020-05-30 /pmc/articles/PMC7321415/ /pubmed/32486173 http://dx.doi.org/10.3390/molecules25112550 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Blachowicz, Tomasz Ehrmann, Andrea Magnetic Elements for Neuromorphic Computing |
title | Magnetic Elements for Neuromorphic Computing |
title_full | Magnetic Elements for Neuromorphic Computing |
title_fullStr | Magnetic Elements for Neuromorphic Computing |
title_full_unstemmed | Magnetic Elements for Neuromorphic Computing |
title_short | Magnetic Elements for Neuromorphic Computing |
title_sort | magnetic elements for neuromorphic computing |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7321415/ https://www.ncbi.nlm.nih.gov/pubmed/32486173 http://dx.doi.org/10.3390/molecules25112550 |
work_keys_str_mv | AT blachowicztomasz magneticelementsforneuromorphiccomputing AT ehrmannandrea magneticelementsforneuromorphiccomputing |