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  5. Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices

Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices

af Ricardo Reis, Luciano Ost, Geancarlo Abich

indgår i Synthesis Lectures on Engineering, Science, and Technology serien

Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices af Ricardo Reis
Bag om Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031185984
  • Indbinding:
  • Hardback
  • Sideantal:
  • 148
  • Udgivet:
  • 2. januar 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 173x14x246 mm.
  • Vægt:
  • 467 g.
  • Ukendt - mangler pt..

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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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