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An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies

The emergence of memristor technologies brings new prospects for modern electronics via enabling novel in-memory computing solutions and energy-efficient and scalable reconfigurable hardware implementations. Several competing memristor technologies have been presented with each bearing distinct perf...

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Autores principales: Stathopoulos, Spyros, Michalas, Loukas, Khiat, Ali, Serb, Alexantrou, Prodromakis, Themis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923392/
https://www.ncbi.nlm.nih.gov/pubmed/31857604
http://dx.doi.org/10.1038/s41598-019-55322-4
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author Stathopoulos, Spyros
Michalas, Loukas
Khiat, Ali
Serb, Alexantrou
Prodromakis, Themis
author_facet Stathopoulos, Spyros
Michalas, Loukas
Khiat, Ali
Serb, Alexantrou
Prodromakis, Themis
author_sort Stathopoulos, Spyros
collection PubMed
description The emergence of memristor technologies brings new prospects for modern electronics via enabling novel in-memory computing solutions and energy-efficient and scalable reconfigurable hardware implementations. Several competing memristor technologies have been presented with each bearing distinct performance metrics across multi-bit memory capacity, low-power operation, endurance, retention and stability. Application needs however are constantly driving the push towards higher performance, which necessitates the introduction of a standard benchmarking procedure for fair evaluation across distinct key metrics. Here we present an electrical characterisation methodology that amalgamates several testing protocols in an appropriate sequence adapted for memristors benchmarking needs, in a technology-agnostic manner. Our approach is designed to extract information on all aspects of device behaviour, ranging from deciphering underlying physical mechanisms to assessing different aspects of electrical performance and even generating data-driven device-specific models. Importantly, it relies solely on standard electrical characterisation instrumentation that is accessible in most electronics laboratories and can thus serve as an independent tool for understanding and designing new memristive device technologies.
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spelling pubmed-69233922019-12-20 An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies Stathopoulos, Spyros Michalas, Loukas Khiat, Ali Serb, Alexantrou Prodromakis, Themis Sci Rep Article The emergence of memristor technologies brings new prospects for modern electronics via enabling novel in-memory computing solutions and energy-efficient and scalable reconfigurable hardware implementations. Several competing memristor technologies have been presented with each bearing distinct performance metrics across multi-bit memory capacity, low-power operation, endurance, retention and stability. Application needs however are constantly driving the push towards higher performance, which necessitates the introduction of a standard benchmarking procedure for fair evaluation across distinct key metrics. Here we present an electrical characterisation methodology that amalgamates several testing protocols in an appropriate sequence adapted for memristors benchmarking needs, in a technology-agnostic manner. Our approach is designed to extract information on all aspects of device behaviour, ranging from deciphering underlying physical mechanisms to assessing different aspects of electrical performance and even generating data-driven device-specific models. Importantly, it relies solely on standard electrical characterisation instrumentation that is accessible in most electronics laboratories and can thus serve as an independent tool for understanding and designing new memristive device technologies. Nature Publishing Group UK 2019-12-19 /pmc/articles/PMC6923392/ /pubmed/31857604 http://dx.doi.org/10.1038/s41598-019-55322-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Stathopoulos, Spyros
Michalas, Loukas
Khiat, Ali
Serb, Alexantrou
Prodromakis, Themis
An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies
title An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies
title_full An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies
title_fullStr An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies
title_full_unstemmed An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies
title_short An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies
title_sort electrical characterisation methodology for benchmarking memristive device technologies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923392/
https://www.ncbi.nlm.nih.gov/pubmed/31857604
http://dx.doi.org/10.1038/s41598-019-55322-4
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