Evangelos Tsipas, Theodoros Panagiotis Chatzinikolaou, Karolos-Alexandros Tsakalos, K. Rallis, Rafailia-Eleni Karamani, Iosif-Angelos Fyrigos, Stavros Kitsios, P. Bousoulas, D. Tsoukalas, G. Sirakoulis
{"title":"Unconventional Memristive Nanodevices","authors":"Evangelos Tsipas, Theodoros Panagiotis Chatzinikolaou, Karolos-Alexandros Tsakalos, K. Rallis, Rafailia-Eleni Karamani, Iosif-Angelos Fyrigos, Stavros Kitsios, P. Bousoulas, D. Tsoukalas, G. Sirakoulis","doi":"10.1109/MNANO.2022.3208789","DOIUrl":null,"url":null,"abstract":"One of the most enticing candidates for next-generation computing systems is the memristor. Memristor-based novel architectures have demonstrated considerable promise in replacing or augmenting traditional computing platforms based on the Von Neumann architecture, which faces many issues in the big-data era, as well as in newly developed neuromorphic tasks. Although the current classical computing architecture is unlikely to be abandoned in the foreseeable future, the growing trend of neuromorphic, quantum, and bio-inspired computing schemes calls for more specialized beyond Von Neumann platforms. Memristors showcase multiple advantages in terms of small area footprint, energy efficiency, high endurance, bio-compatibility, and their inherent synaptic and neuromorphic behavior. The topic of this work is to present the memristive devices that meet the requirements for the implementation of the novel beyond Von Neumann applications and examine their switching mechanism and material selection, as well as to conduct a performance comparison between the fabricated devices paving the way for future computing applications.","PeriodicalId":44724,"journal":{"name":"IEEE Nanotechnology Magazine","volume":"16 1","pages":"34-45"},"PeriodicalIF":2.3000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Nanotechnology Magazine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MNANO.2022.3208789","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NANOSCIENCE & NANOTECHNOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
One of the most enticing candidates for next-generation computing systems is the memristor. Memristor-based novel architectures have demonstrated considerable promise in replacing or augmenting traditional computing platforms based on the Von Neumann architecture, which faces many issues in the big-data era, as well as in newly developed neuromorphic tasks. Although the current classical computing architecture is unlikely to be abandoned in the foreseeable future, the growing trend of neuromorphic, quantum, and bio-inspired computing schemes calls for more specialized beyond Von Neumann platforms. Memristors showcase multiple advantages in terms of small area footprint, energy efficiency, high endurance, bio-compatibility, and their inherent synaptic and neuromorphic behavior. The topic of this work is to present the memristive devices that meet the requirements for the implementation of the novel beyond Von Neumann applications and examine their switching mechanism and material selection, as well as to conduct a performance comparison between the fabricated devices paving the way for future computing applications.
期刊介绍:
IEEE Nanotechnology Magazine publishes peer-reviewed articles that present emerging trends and practices in industrial electronics product research and development, key insights, and tutorial surveys in the field of interest to the member societies of the IEEE Nanotechnology Council. IEEE Nanotechnology Magazine will be limited to the scope of the Nanotechnology Council, which supports the theory, design, and development of nanotechnology and its scientific, engineering, and industrial applications.