Titlebook: Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Const; Geancarlo Abich,Luciano Ost,Ricardo

察覺

Geancarlo Abich,Luciano Ost,Ricardo ReisDescribes a virtual platform framework (i.e., SOFIA) to conduct soft error reliability assessment of CNN software.Uses novel fault injection techniques to assess the impact of CNN models running in re

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小丑

https://doi.org/10.1007/978-3-031-18599-1software reliability; soft error analysis; Fault Injection; Machine Learning Applied to Soft Error Asse

擔(dān)心

aviator

Background in ML Models and Radiation Effects,s. First, Sect.?2.1 presents a background in ML models and the challenges to enable the execution of such models in IoT edge devices. Further, Sect.?2.2 addresses the basic concepts regarding radiation-induced errors and their impact on electronic computing system devices.

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離開可分裂

Fortify

Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Const978-3-031-18599-1Series ISSN 2690-0300 Series E-ISSN 2690-0327

構(gòu)想

https://doi.org/10.1007/978-3-322-97014-5s. First, Sect.?2.1 presents a background in ML models and the challenges to enable the execution of such models in IoT edge devices. Further, Sect.?2.2 addresses the basic concepts regarding radiation-induced errors and their impact on electronic computing system devices.

食草

Peter Bruhns,Hands-Georg Glasemann multi-core systems (Sect.?.). In this sense, each fault injection module is detailed to show its usefulness, that is, RTL (Sect.?.), gem5 (Sect.?.), and Open Virtual Platform Simulator (OVPsim) (Sect.?.).