{"title":"基于NAND闪存的三维神经形态计算系统的辐射耐受性","authors":"M. Hasan, M. Raquibuzzaman, I. Chatterjee, B. Ray","doi":"10.1109/IRPS45951.2020.9128219","DOIUrl":null,"url":null,"abstract":"In this paper we show the effectiveness of a multi-level-cell 3-D NAND flash chip as a weight storage device for a neuromorphic computing system under radiation environment. We find that the error-correction codes can be avoided for storing model weights in 3-D NAND for enabling low-power computing applications without sacrificing much accuracy (radiation dose <10k rad). Additionally, radiation induced BER data shows layer-to-layer variations, which can be utilized in favor of improving neural network’s accuracy.","PeriodicalId":116002,"journal":{"name":"2020 IEEE International Reliability Physics Symposium (IRPS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Radiation Tolerance of 3-D NAND Flash Based Neuromorphic Computing System\",\"authors\":\"M. Hasan, M. Raquibuzzaman, I. Chatterjee, B. Ray\",\"doi\":\"10.1109/IRPS45951.2020.9128219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we show the effectiveness of a multi-level-cell 3-D NAND flash chip as a weight storage device for a neuromorphic computing system under radiation environment. We find that the error-correction codes can be avoided for storing model weights in 3-D NAND for enabling low-power computing applications without sacrificing much accuracy (radiation dose <10k rad). Additionally, radiation induced BER data shows layer-to-layer variations, which can be utilized in favor of improving neural network’s accuracy.\",\"PeriodicalId\":116002,\"journal\":{\"name\":\"2020 IEEE International Reliability Physics Symposium (IRPS)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Reliability Physics Symposium (IRPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRPS45951.2020.9128219\",\"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 IEEE International Reliability Physics Symposium (IRPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRPS45951.2020.9128219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Radiation Tolerance of 3-D NAND Flash Based Neuromorphic Computing System
In this paper we show the effectiveness of a multi-level-cell 3-D NAND flash chip as a weight storage device for a neuromorphic computing system under radiation environment. We find that the error-correction codes can be avoided for storing model weights in 3-D NAND for enabling low-power computing applications without sacrificing much accuracy (radiation dose <10k rad). Additionally, radiation induced BER data shows layer-to-layer variations, which can be utilized in favor of improving neural network’s accuracy.
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