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"item_title" : "Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained Iot Edge Devices",
"item_author" : [" Geancarlo Abich", "Luciano Ost", "Ricardo Reis "],
"item_description" : "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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Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained Iot Edge Devices
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Overview
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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Details
- ISBN-13: 9783031185984
- ISBN-10: 3031185986
- Publisher: Springer
- Publish Date: January 2023
- Dimensions: 9.37 x 6.38 x 0.39 inches
- Shipping Weight: 0.95 pounds
- Page Count: 131
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