| 書目名稱 | Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Const |
| 編輯 | Geancarlo Abich,Luciano Ost,Ricardo Reis |
| 視頻video | http://file.papertrans.cn/301/300808/300808.mp4 |
| 概述 | Describes 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 |
| 叢書名稱 | Synthesis Lectures on Engineering, Science, and Technology |
| 圖書封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2023 |
| 關(guān)鍵詞 | software reliability; soft error analysis; Fault Injection; Machine Learning Applied to Soft Error Asse |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-18599-1 |
| isbn_softcover | 978-3-031-18601-1 |
| isbn_ebook | 978-3-031-18599-1Series ISSN 2690-0300 Series E-ISSN 2690-0327 |
| issn_series | 2690-0300 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機(jī)版|小黑屋|
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