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Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices (Synthesis Lectures on Engineering, Science, and Technology)

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Book Details
Language
English
Publishers
Springer; 1st ed. 2023 edition (3 Jan. 2024)
Weight
0.25 KG
Publication Date
03/01/2024
ISBN-10
303118601X
Pages
146 pages
ISBN-13
9783031186011
Dimensions
16.8 x 0.86 x 24 cm
SKU
9783031186011
Author Name
Geancarlo Abich (Author)
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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.

. .

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