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

造反,叛亂

https://doi.org/10.1007/978-3-322-84893-2on of ML inference models executing on resource-constrained IoT edge devices. The underlying contribution has been published in several international conferences [.,.,.] and high quality journals [., .].

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?kologische Unternehmenspolitikvements in internet protocols and the computational efficiency of emerging technologies have made communication between different devices more accessible than before [1]. Recent reports, from communication technology enterprises [2] estimate that there will be around 25–32 billion devices connected

nugatory

創(chuàng)造性

,Beitrag der neoklassischen Umwelt?konomie,efinitions from Avi?ienis et al. [1] for fault, error, and failure. A fault is an event that may cause the internal state of the system to change, e.g., a radiation particle strike. When a fault affects the system’s internal state, it becomes an error. If the error causes a deviation of at least one

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Andrea Dagef?rde,Reinhard F. Hüttlon framework. This work has investigated the soft error assessment consistency of a JIT virtual platform simulator (SOFIA) with more than 12 million fault injections considering single and multi-core Arm processor architectures. The fault injection campaigns considered different cross-compilers, sof

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avarice

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