harDNNing: a machine-learning-based framework for fault tolerance assessment and protection of DNNs
Author:
Affiliation:
1. Inria, Univ Rennes, CNRS, IRISA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10173930/10173940/10174178.pdf?arnumber=10174178
Reference29 articles.
1. Understanding error propagation in deep learning neural network (DNN) accelerators and applications
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3. Efficient Fault-Criticality Analysis for AI Accelerators using a Neural Twin∗
4. Fast and Accurate Error Simulation for CNNs Against Soft Errors
5. On the Resilience of RTL NN Accelerators: Fault Characterization and Mitigation
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