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Conference Paper: Large Memristor Crossbars for Analog Computing

TitleLarge Memristor Crossbars for Analog Computing
Authors
KeywordsMemristor
Resistance switching
Analog computing
Signal processing
Image processing
Vector matrix multiplication
Issue Date2018
Citation
Proceedings - IEEE International Symposium on Circuits and Systems, 2018, v. 2018-May How to Cite?
Abstract© 2018 IEEE. Memristor with tunable non-volatile resistance offers in-memory computing capability that avoids the von-Neumann bottleneck. However, large-scale experimental demonstration to this end is yet to be implemented due to the immaturity of the device and integration technologies. Here in this paper we report our recent process in analog computing using analog-voltage-amplitude-vector input and analog-memristor-conductance matrix, with applications in signal and image processing. The vector matrix multiplication is processed in the memristor crossbars in one step, with 5-8 bit precision depending on the array size. The demonstration is made possible by high memristor yield (99.8%), stable multilevel memresistance states, linear current-voltage (IV) relation in the operation range, and low wire resistance between the cells.
Persistent Identifierhttp://hdl.handle.net/10722/286978
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLi, Can-
dc.contributor.authorLi, Yunning-
dc.contributor.authorJiang, Hao-
dc.contributor.authorSong, Wenhao-
dc.contributor.authorLin, Peng-
dc.contributor.authorWang, Zhongrui-
dc.contributor.authorYang, J. Joshua-
dc.contributor.authorXia, Qiangfei-
dc.contributor.authorHu, Miao-
dc.contributor.authorMontgomery, Eric-
dc.contributor.authorZhang, Jiaming-
dc.contributor.authorDavila, Noraica-
dc.contributor.authorGraves, Catherine E.-
dc.contributor.authorLi, Zhiyong-
dc.contributor.authorStrachan, John Paul-
dc.contributor.authorWilliams, R. Stanley-
dc.contributor.authorGe, Ning-
dc.contributor.authorBarnell, Mark-
dc.contributor.authorWu, Qing-
dc.date.accessioned2020-09-07T11:46:10Z-
dc.date.available2020-09-07T11:46:10Z-
dc.date.issued2018-
dc.identifier.citationProceedings - IEEE International Symposium on Circuits and Systems, 2018, v. 2018-May-
dc.identifier.issn0271-4310-
dc.identifier.urihttp://hdl.handle.net/10722/286978-
dc.description.abstract© 2018 IEEE. Memristor with tunable non-volatile resistance offers in-memory computing capability that avoids the von-Neumann bottleneck. However, large-scale experimental demonstration to this end is yet to be implemented due to the immaturity of the device and integration technologies. Here in this paper we report our recent process in analog computing using analog-voltage-amplitude-vector input and analog-memristor-conductance matrix, with applications in signal and image processing. The vector matrix multiplication is processed in the memristor crossbars in one step, with 5-8 bit precision depending on the array size. The demonstration is made possible by high memristor yield (99.8%), stable multilevel memresistance states, linear current-voltage (IV) relation in the operation range, and low wire resistance between the cells.-
dc.languageeng-
dc.relation.ispartofProceedings - IEEE International Symposium on Circuits and Systems-
dc.subjectMemristor-
dc.subjectResistance switching-
dc.subjectAnalog computing-
dc.subjectSignal processing-
dc.subjectImage processing-
dc.subjectVector matrix multiplication-
dc.titleLarge Memristor Crossbars for Analog Computing-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ISCAS.2018.8351877-
dc.identifier.scopuseid_2-s2.0-85057121006-
dc.identifier.volume2018-May-
dc.identifier.spagenull-
dc.identifier.epagenull-
dc.identifier.issnl0271-4310-

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