Selective Hardening of CNNs based on Layer Vulnerability Estimation

التفاصيل البيبلوغرافية
العنوان: Selective Hardening of CNNs based on Layer Vulnerability Estimation
المؤلفون: Bolchini C., Cassano L., Miele A., Nazzari A.
المساهمون: Bolchini, C., Cassano, L., Miele, A., Nazzari, A.
بيانات النشر: Institute of Electrical and Electronics Engineers Inc.
سنة النشر: 2022
المجموعة: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano
مصطلحات موضوعية: Convolutional Neural Networks, Functional Vulnerability Factor, Reliability Analysis, Selective Hardening
الوصف: There is an increasing interest in employing Convolutional Neural Networks (CNNs) in safety-critical application fields. In such scenarios, it is vital to ensure that the application fulfills the reliability requirements expressed by customers and design standards. On the other hand, given the CNNs extremely high computational requirements, it is also paramount to achieve high performance. To meet both reliability and performance requirements, partial and selective replication of the layers of the CNN can be applied. In this paper, we identify the most critical layers of a CNN in terms of vulnerability to fault and selectively duplicate them to achieve a target reliability vs. execution time trade-off. To this end we perform a design space exploration to identify layers to be duplicated. Results on the application of the proposed approach to four case study CNNs are reported.
نوع الوثيقة: conference object
وصف الملف: ELETTRONICO
اللغة: English
العلاقة: info:eu-repo/semantics/altIdentifier/isbn/978-1-6654-5938-9; ispartofbook:Proceedings - IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT; 35th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT 2022; volume:2022; firstpage:1; lastpage:6; numberofpages:6; https://hdl.handle.net/11311/1230506Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85143818474
DOI: 10.1109/DFT56152.2022.9962339
الإتاحة: https://doi.org/10.1109/DFT56152.2022.9962339Test
https://hdl.handle.net/11311/1230506Test
حقوق: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.780AF214
قاعدة البيانات: BASE