FTT-NAS: Discovering Fault-Tolerant Neural Architecture

Pages: 211 - 216
Published: Jan 1, 2020
Abstract
With the fast evolvement of deep-learning specific embedded computing systems, applications powered by deep learning are moving from the cloud to the edge. When deploying NNs onto the edge devices under complex environments, there are various types of possible faults: soft errors caused by atmospheric neutrons and radioactive impurities, voltage instability, aging, temperature variations, and malicious attackers. Thus the safety risk of...
Paper Details
Title
FTT-NAS: Discovering Fault-Tolerant Neural Architecture
Published Date
Jan 1, 2020
Journal
Pages
211 - 216
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