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GPU-enabled back-propagation artificial neural network for digit recognition in parallel
Ricardo Brito1; Simon Fong1; Kyungeun Cho2; Wei Song3; Raymond Wong4; Sabah Mohammed5; Jinan Fiaidhi5
2016-10-01
Source PublicationJournal of Supercomputing
ISSN0920-8542
Volume72Issue:10Pages:3868-3886
Abstract

In this paper, we show that the GPU (graphics processing unit) can be used not only for processing graphics, but also for high speed computing. We provide a comparison between the times taken on the CPU and GPU to perform the training and testing of a back-propagation artificial neural network. We implemented two neural networks for recognizing handwritten digits; one consists of serial code executed on the CPU, while the other is a GPU-based version of the same system which executes in parallel. As an experiment for performance evaluation, a system for neural network training on the GPU is developed to reduce training time. The programming environment that the system is based on is CUDA which stands for compute unified device architecture, which allows a programmer to write code that will run on an NVIDIA GPU card. Our results over an experiment of digital image recognition using neural network confirm the speed-up advantages by tapping on the resources of GPU. Our proposed model has an advantage of simplicity, while it shows on par performance with the state-of-the-arts algorithms.

KeywordArtificial Neural Networks Cuda Nvidia Parallel Execution
DOIhttps://doi.org/10.1007/s11227-016-1633-y
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000385417400011
PublisherSPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
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Cited Times [WOS]:4   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorRicardo Brito; Simon Fong; Kyungeun Cho; Wei Song; Raymond Wong; Sabah Mohammed; Jinan Fiaidhi
Affiliation1.Department of Computer and Information Science, University of Macau, Macau SAR, China
2.Department of Computer and Multimedia Engineering, Dongguk University, Seoul, Korea
3.College of Information Engineering, North China University of Technology, Beijing, China
4.School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
5.Department of Computer Science, Lakehead University, Thunder Bay, Canada
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ricardo Brito,Simon Fong,Kyungeun Cho,et al. GPU-enabled back-propagation artificial neural network for digit recognition in parallel[J]. Journal of Supercomputing,2016,72(10):3868-3886.
APA Ricardo Brito.,Simon Fong.,Kyungeun Cho.,Wei Song.,Raymond Wong.,...&Jinan Fiaidhi.(2016).GPU-enabled back-propagation artificial neural network for digit recognition in parallel.Journal of Supercomputing,72(10),3868-3886.
MLA Ricardo Brito,et al."GPU-enabled back-propagation artificial neural network for digit recognition in parallel".Journal of Supercomputing 72.10(2016):3868-3886.
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