{"title":"具有可扩展LEE Flash®-G2 SONOS的高性价比嵌入式非易失性存储器，适用于安全物联网和内存中计算(CiM)应用","authors":"K. Nii, Y. Taniguchi, K. Okuyama","doi":"10.1109/VLSI-DAT49148.2020.9196270","DOIUrl":null,"url":null,"abstract":"We introduce a cost-effective, reliable and energy efficient embedded flash memory technology and its applications. A charge trapping type of Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) with twin select-gates structure has been demonstrated on 55-nm bulk CMOS technology. It is potentially scalable on advanced fully depleted (FD)-SOI or 3D Fin-FET devices below 28-nm node. Those feasibilities are shown by TCAD simulations and existing 55-nm planar bulk silicon data. Secure and low-power applications are introduced that are using nonvolatile (NV)-SRAM by combining with SRAM cell and flash cell. Besides, analog computing-inmemory (CiM) based on flash is also introduced for energy efficient artificial intelligence (AI) applications in edge computing.","PeriodicalId":235460,"journal":{"name":"2020 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","volume":"310 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Cost-Effective Embedded Nonvolatile Memory with Scalable LEE Flash®-G2 SONOS for Secure IoT and Computing-in-Memory (CiM) Applications\",\"authors\":\"K. Nii, Y. Taniguchi, K. Okuyama\",\"doi\":\"10.1109/VLSI-DAT49148.2020.9196270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a cost-effective, reliable and energy efficient embedded flash memory technology and its applications. A charge trapping type of Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) with twin select-gates structure has been demonstrated on 55-nm bulk CMOS technology. It is potentially scalable on advanced fully depleted (FD)-SOI or 3D Fin-FET devices below 28-nm node. Those feasibilities are shown by TCAD simulations and existing 55-nm planar bulk silicon data. Secure and low-power applications are introduced that are using nonvolatile (NV)-SRAM by combining with SRAM cell and flash cell. Besides, analog computing-inmemory (CiM) based on flash is also introduced for energy efficient artificial intelligence (AI) applications in edge computing.\",\"PeriodicalId\":235460,\"journal\":{\"name\":\"2020 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)\",\"volume\":\"310 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VLSI-DAT49148.2020.9196270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSI-DAT49148.2020.9196270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Cost-Effective Embedded Nonvolatile Memory with Scalable LEE Flash®-G2 SONOS for Secure IoT and Computing-in-Memory (CiM) Applications
We introduce a cost-effective, reliable and energy efficient embedded flash memory technology and its applications. A charge trapping type of Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) with twin select-gates structure has been demonstrated on 55-nm bulk CMOS technology. It is potentially scalable on advanced fully depleted (FD)-SOI or 3D Fin-FET devices below 28-nm node. Those feasibilities are shown by TCAD simulations and existing 55-nm planar bulk silicon data. Secure and low-power applications are introduced that are using nonvolatile (NV)-SRAM by combining with SRAM cell and flash cell. Besides, analog computing-inmemory (CiM) based on flash is also introduced for energy efficient artificial intelligence (AI) applications in edge computing.
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