Analyzing the resilience of convolutional neural networks implemented on GPUs: Alexnet as a case study

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Analyzing the resilience of convolutional neural networks implemented on GPUs: Alexnet as a case study

There have been an extensive use of Convolutional Neural Networks (CNNs) in healthcare applications. Presently, GPUs are the most prominent and dominated DNN accelerators to increase the execution speed of CNN algorithms to improve their performance as well as the Latency. However, GPUs are prone to...

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Bibliographic Details
Main Authors:	Khalid Adam, Ismail Hammad, Izzeldin, I. Mohd, Ibrahim, Younis
Format:	Article
Language:	English
Published:	Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek 2021
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/32465/ http://umpir.ump.edu.my/id/eprint/32465/1/Analyzing%20the%20resilience%20of%20convolutional%20neural%20networks%20implemented%20on%20GPUs.pdf

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