Analyzing and Increasing the Reliability of Convolutional Neural Networks on GPUs-Reference-Cited by-同舟云学术

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Analyzing and Increasing the Reliability of Convolutional Neural Networks on GPUs

Published:2019-06 Issue:2 Volume:68 Page:663-677
ISSN:0018-9529
Container-title:IEEE Transactions on Reliability
language:
Short-container-title:IEEE Trans. Rel.

Author:

Santos Fernando Fernandes dos^ORCID,Pimenta Pedro Foletto,Lunardi Caio^ORCID,Draghetti Lucas,Carro Luigi^ORCID,Kaeli David^ORCID,Rech Paolo^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/24/8727549/08536419.pdf?arnumber=8536419

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1. Evaluating single event upsets in deep neural networks for semantic segmentation: An embedded system perspective;Journal of Systems Architecture;2024-09

2. Transient Fault Detection in Tensor Cores for Modern GPUs;ACM Transactions on Embedded Computing Systems;2024-08-28

3. ALPRI-FI: A Framework for Early Assessment of Hardware Fault Resiliency of DNN Accelerators;Electronics;2024-08-15

4. A characterization of soft-error sensitivity in data-parallel and model-parallel distributed deep learning;Journal of Parallel and Distributed Computing;2024-08

5. Analyzing the Influence of Memory and Workload on the Reliability of GPUs Under Neutron Radiation;IEEE Transactions on Nuclear Science;2024-08

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