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	An adaptive synchronous parallel strategy for distributed machine learning
	Zhang, Jilin1,2,3,4,5; Tu, Hangdi1,2; Ren, Yongjian1,2; Wan, Jian1,2,4,5; Zhou, Li1,2; Li, Mingwei1,2; Wang, Jue6
刊名	Ieee access
	2018
卷号	6页码:19222-19230
关键词	Distributed machine learning Adaptive synchronous parallel Communication strategy Parameter server
ISSN号	2169-3536
DOI	10.1109/access.2018.2820899
通讯作者	Ren, yongjian(yongjian.ren@hdu.edu.cn)
英文摘要	In recent years, distributed systems have mainly been used to train machine learning (ml) models. however, as a result of the different performances among computational nodes in a distributed cluster and delays in network transmission, the accuracies and convergence rates of ml models are relatively low. therefore, it is necessary to design a reasonable strategy that provides dynamic communication optimization to improve the utilization of the cluster, accelerate the training times, and strengthen the accuracy of the training model. in this paper, we propose the adaptive synchronous parallel strategy for distributed ml. through the performance monitoring model, the synchronization strategy of each computational node with the parameter server is adjusted adaptively by considering the full performance of each node, thereby ensuring higher accuracy. furthermore, our strategy prevents the ml model from being affected by irrelevant tasks in the same cluster. experiments show that our strategy fully improves clustering performance, and it ensures the accuracy and convergence speed of the model, increases the model training speed, and has good expansibility.
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000430941500001
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2374232
专题	计算机网络信息中心
通讯作者	Ren, Yongjian
作者单位	1.Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou 310018, Zhejiang, Peoples R China 2.Minist Educ, Key Lab Complex Syst Modeling & Simulat, Hangzhou 310018, Zhejiang, Peoples R China 3.Zhejiang Univ, Coll Elect Engn, Hangzhou 310058, Zhejiang, Peoples R China 4.Zhejiang Univ Sci & Technol, Sch Informat & Elect Engn, Hangzhou 310023, Zhejiang, Peoples R China 5.Zhejiang Prov Engn Ctr Media Data Cloud Proc & An, Hangzhou 310018, Zhejiang, Peoples R China 6.Chinese Acad Sci, Supercomp Ctr Comp Network Informat Ctr, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Jilin,Tu, Hangdi,Ren, Yongjian,et al. An adaptive synchronous parallel strategy for distributed machine learning[J]. Ieee access,2018,6:19222-19230.
APA	Zhang, Jilin.,Tu, Hangdi.,Ren, Yongjian.,Wan, Jian.,Zhou, Li.,...&Wang, Jue.(2018).An adaptive synchronous parallel strategy for distributed machine learning.Ieee access,6,19222-19230.
MLA	Zhang, Jilin,et al."An adaptive synchronous parallel strategy for distributed machine learning".Ieee access 6(2018):19222-19230.

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