Analyzing the reliability of convolutional neural networks on GPUs : GoogLeNet as a case study
Convolutional Neural Networks (CNNs) are used for tasks such as object recognition. Once a CNN model is used in a radiative environment, reliability of the system against soft errors is a crucial issue, especially in safety-critical and high-performance applications that bound with real-time respons...
Main Authors: | , , |
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Format: | Conference or Workshop Item |
Language: | English English |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2020
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Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/42444/1/Analyzing%20the%20reliability%20of%20convolutional%20neural%20networks%20on%20GPUs.pdf http://umpir.ump.edu.my/id/eprint/42444/2/Analyzing%20the%20reliability%20of%20convolutional%20neural%20networks%20on%20GPUs_GoogLeNet%20as%20a%20case%20study_ABS.pdf |
Internet
http://umpir.ump.edu.my/id/eprint/42444/1/Analyzing%20the%20reliability%20of%20convolutional%20neural%20networks%20on%20GPUs.pdfhttp://umpir.ump.edu.my/id/eprint/42444/2/Analyzing%20the%20reliability%20of%20convolutional%20neural%20networks%20on%20GPUs_GoogLeNet%20as%20a%20case%20study_ABS.pdf