C. Tung, Biresh Kumar Joardar, P. Pande, J. Doppa, Hai Helen Li, K. Chakrabarty
{"title":"基于ReRAM横梁的CNN可靠训练动态任务映射","authors":"C. Tung, Biresh Kumar Joardar, P. Pande, J. Doppa, Hai Helen Li, K. Chakrabarty","doi":"10.23919/DATE56975.2023.10137238","DOIUrl":null,"url":null,"abstract":"A ReRAM crossbar-based computing system (RCS) can accelerate CNN training. However, hardware faults due to manufacturing defects and limited endurance impede the widespread adoption of RCS. We propose a dynamic task remapping-based technique for reliable CNN training on faulty RCS. Experimental results demonstrate that the proposed low-overhead method incurs only 0.85% accuracy loss on average while training popular CNNs such as VGGs, ResNets, and SqueezeNet with the CIFAR-IO, CIFAR-100, and SVHN datasets in the presence of faults.","PeriodicalId":340349,"journal":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic Task Remapping for Reliable CNN Training on ReRAM Crossbars\",\"authors\":\"C. Tung, Biresh Kumar Joardar, P. Pande, J. Doppa, Hai Helen Li, K. Chakrabarty\",\"doi\":\"10.23919/DATE56975.2023.10137238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A ReRAM crossbar-based computing system (RCS) can accelerate CNN training. However, hardware faults due to manufacturing defects and limited endurance impede the widespread adoption of RCS. We propose a dynamic task remapping-based technique for reliable CNN training on faulty RCS. Experimental results demonstrate that the proposed low-overhead method incurs only 0.85% accuracy loss on average while training popular CNNs such as VGGs, ResNets, and SqueezeNet with the CIFAR-IO, CIFAR-100, and SVHN datasets in the presence of faults.\",\"PeriodicalId\":340349,\"journal\":{\"name\":\"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/DATE56975.2023.10137238\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/DATE56975.2023.10137238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Task Remapping for Reliable CNN Training on ReRAM Crossbars
A ReRAM crossbar-based computing system (RCS) can accelerate CNN training. However, hardware faults due to manufacturing defects and limited endurance impede the widespread adoption of RCS. We propose a dynamic task remapping-based technique for reliable CNN training on faulty RCS. Experimental results demonstrate that the proposed low-overhead method incurs only 0.85% accuracy loss on average while training popular CNNs such as VGGs, ResNets, and SqueezeNet with the CIFAR-IO, CIFAR-100, and SVHN datasets in the presence of faults.