Scheduling-Efficient Framework for Neural Network on Heterogeneous Distributed Systems and Mobile Edge Computing Systems | |
Zhou, Xiang1,2; Zhang, Jilin1,2,4; Wan, Jian1,2,3; Zhou, Li1,2; Wei, Zhenguo5; Zhang, Juncong5 | |
刊名 | IEEE ACCESS
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2019 | |
卷号 | 7页码:171853-171863 |
关键词 | Heterogeneous distributed system mobile edge computing system adaptive scheduling large-scale machine learning |
ISSN号 | 2169-3536 |
DOI | 10.1109/ACCESS.2019.2954897 |
英文摘要 | As the volume of machine learning training data sets and the quantity of model parameters continue to grow, the pattern in which machine learning models are trained alone can no longer accommodate large-scale data environments. However, distributed systems and mobile edge computing systems are unpredictable and have heterogeneous nodes, resulting in interruptions in training or low convergence rate. In addition, existing distributed machine learning frameworks cannot guarantee a good convergence rate and speedup ratio in a variety of operating environments. Considering the above shortcomings, this paper proposes an adaptive scheduling framework for machine learning based on a heterogeneous distributed system and mobile edge computing system for machine learning model optimization. The framework detects and analyzes the dynamic changes of resources in the distributed system and mobile edge computing system through the resource detection system; then, the task scheduling system adaptively modifies the environmental parameters and schedules calculations. Relevant experiments conducted with the public data set show that the robustness and scalability of the framework are significantly better than the traditional distributed machine learning framework under the premise of ensuring high convergence rate. |
资助项目 | National Key Technology Research and Development Program[2018YFB0204001] ; National Natural Science Foundation of China[61672200] ; National Natural Science Foundation of China[61572163] ; Key Technology Research and Development Program of the Zhejiang Province[2019C01059] ; Key Technology Research and Development Program of the Zhejiang Province[2019C03135] ; Key Technology Research and Development Program of the Zhejiang Province[2019C03134] ; Zhejiang Natural Science Funds[LY-17F020029] ; State Key Laboratory of Computer Architecture[CARCH201712] ; Hangzhou Dianzi University Postgraduate Research Innovation Fund Program[CXJJ2018052] |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000509374200039 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/14710] ![]() |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Zhang, Jilin; Wan, Jian |
作者单位 | 1.Hangzhou Dianzi Univ, Sch Comp, Hangzhou 310018, Peoples R China 2.Minist Educ, Key Lab Complex Syst Modeling & Simulat, Hangzhou 310018, Peoples R China 3.Zhejiang Univ Sci & Technol, Sch Comp Sci & Technol, Hangzhou 310023, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 5.Zhejiang Dawning Informat Technol Co Ltd, Hangzhou 310051, Peoples R China |
推荐引用方式 GB/T 7714 | Zhou, Xiang,Zhang, Jilin,Wan, Jian,et al. Scheduling-Efficient Framework for Neural Network on Heterogeneous Distributed Systems and Mobile Edge Computing Systems[J]. IEEE ACCESS,2019,7:171853-171863. |
APA | Zhou, Xiang,Zhang, Jilin,Wan, Jian,Zhou, Li,Wei, Zhenguo,&Zhang, Juncong.(2019).Scheduling-Efficient Framework for Neural Network on Heterogeneous Distributed Systems and Mobile Edge Computing Systems.IEEE ACCESS,7,171853-171863. |
MLA | Zhou, Xiang,et al."Scheduling-Efficient Framework for Neural Network on Heterogeneous Distributed Systems and Mobile Edge Computing Systems".IEEE ACCESS 7(2019):171853-171863. |
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