Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Const

Name: Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Const
Brand: Springer Nature
SKU: 9783031185991
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Springer Nature

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9783031185991

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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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