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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.
| Autorius: | Geancarlo Abich, Ricardo Reis, Luciano Ost, |
| Serija: | Synthesis Lectures on Engineering, Science, and Technology |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2024 |
| Knygos puslapių skaičius: | 148 |
| ISBN-10: | 303118601X |
| ISBN-13: | 9783031186011 |
| Formatas: | 240 x 168 x 9 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices“
