A Parallel Strategy for Convolutional Neural Network Based on Heterogeneous Cluster for Mobile Information System
Joint Authors
Ren, Yongjian
Wan, Jian
Zhou, Li
Zhang, Jilin
Xiao, Junfeng
Si, Huayou
Tu, Hangdi
Yang, Jianhua
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-21
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Telecommunications Engineering
Abstract EN
With the development of the mobile systems, we gain a lot of benefits and convenience by leveraging mobile devices; at the same time, the information gathered by smartphones, such as location and environment, is also valuable for business to provide more intelligent services for customers.
More and more machine learning methods have been used in the field of mobile information systems to study user behavior and classify usage patterns, especially convolutional neural network.
With the increasing of model training parameters and data scale, the traditional single machine training method cannot meet the requirements of time complexity in practical application scenarios.
The current training framework often uses simple data parallel or model parallel method to speed up the training process, which is why heterogeneous computing resources have not been fully utilized.
To solve these problems, our paper proposes a delay synchronization convolutional neural network parallel strategy, which leverages the heterogeneous system.
The strategy is based on both synchronous parallel and asynchronous parallel approaches; the model training process can reduce the dependence on the heterogeneous architecture in the premise of ensuring the model convergence, so the convolution neural network framework is more adaptive to different heterogeneous system environments.
The experimental results show that the proposed delay synchronization strategy can achieve at least three times the speedup compared to the traditional data parallelism.
American Psychological Association (APA)
Zhang, Jilin& Xiao, Junfeng& Wan, Jian& Yang, Jianhua& Ren, Yongjian& Si, Huayou…[et al.]. 2017. A Parallel Strategy for Convolutional Neural Network Based on Heterogeneous Cluster for Mobile Information System. Mobile Information Systems،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1189040
Modern Language Association (MLA)
Zhang, Jilin…[et al.]. A Parallel Strategy for Convolutional Neural Network Based on Heterogeneous Cluster for Mobile Information System. Mobile Information Systems No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1189040
American Medical Association (AMA)
Zhang, Jilin& Xiao, Junfeng& Wan, Jian& Yang, Jianhua& Ren, Yongjian& Si, Huayou…[et al.]. A Parallel Strategy for Convolutional Neural Network Based on Heterogeneous Cluster for Mobile Information System. Mobile Information Systems. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1189040
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189040