Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices / Synthesis Lectures on Engineering, Science, and Technology (PDF)
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This book describes an extensive and consistent soft error assessment of convolutional neural network (CNN) models from different domains through more than 14.8 million fault injections, considering different precision bit-width configurations, optimization parameters, and processor models. The authors also evaluate the relative performance, memory utilization, and soft error reliability trade-offs analysis of different CNN models considering a compiler-based technique w.r.t. traditional redundancy approaches.
Luciano Ost is currently a Faculty Member with Loughborough University's Wolfson School - UK. He received his Ph.D. in Computer Science from PUCRS, Brazil in 2010. During his Ph.D., Dr Ost worked as an invited researcher at the Microelectronic Systems Institute of the Technische Universitaet Darmstadt (from 2007 to 2008) and at the University of York (October 2009). After completing his doctorate, he worked as a research assistant (2 years) and then as an assistant professor (2 years) at the University of Montpellier II in France. He has authored more than 90 papers, and his research is devoted to advancing hardware and software architectures to improve the performance, security, and reliability of machine learning and life-critical embedded systems.
Ricardo Reis received the Electrical Engineering degree from the Federal University of Rio Grande do Sul (UFRGS), Brazil, in 1978, and the Ph.D. degree in informatics, option microelectronics from the Institut National Polytechnique de Grenoble, France, in 1983. He received the Doctor Honoris Causa from University of Montpellier, France, in 2016. He has been a Full Professor with UFRGS since 1981. He is at research level 1A of the CNPq (Brazilian National Science Foundation), and the head of several research
- Autoren: Geancarlo Abich , Luciano Ost , Ricardo Reis
- 2023, 1st ed. 2023, 131 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3031185994
- ISBN-13: 9783031185991
- Erscheinungsdatum: 01.01.2023
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