TransGPerf: Exploiting Transfer Learning for Modeling Distributed Graph Computation Performance

doi:10.1007/s11390-021-1356-2

	TransGPerf: Exploiting Transfer Learning for Modeling Distributed Graph Computation Performance
	Niu, Songjie ; Chen, Shimin 1
刊名	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
	2021-07-01
卷号	36 期号:4 页码:778-791
关键词	performance modeling distributed graph computation deep learning transfer learning
ISSN号	1000-9000
DOI	10.1007/s11390-021-1356-2
英文摘要	It is challenging to model the performance of distributed graph computation. Explicit formulation cannot easily capture the diversified factors and complex interactions in the system. Statistical learning methods require a large number of training samples to generate an accurate prediction model. However, it is time-consuming to run the required graph computation tests to obtain the training samples. In this paper, we propose TransGPerf, a transfer learning based solution that can exploit prior knowledge from a source scenario and utilize a manageable amount of training data for modeling the performance of a target graph computation scenario. Experimental results show that our proposed method is capable of generating accurate models for a wide range of graph computation tasks on PowerGraph and GraphX. It outperforms transfer learning methods proposed for other applications in the literature.
WOS研究方向	Computer Science
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000684229900005
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/17301]
专题	中国科学院计算技术研究所
通讯作者	Chen, Shimin
作者单位	1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Niu, Songjie,Chen, Shimin. TransGPerf: Exploiting Transfer Learning for Modeling Distributed Graph Computation Performance[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2021,36(4):778-791.
APA	Niu, Songjie,&Chen, Shimin.(2021).TransGPerf: Exploiting Transfer Learning for Modeling Distributed Graph Computation Performance.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,36(4),778-791.
MLA	Niu, Songjie,et al."TransGPerf: Exploiting Transfer Learning for Modeling Distributed Graph Computation Performance".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 36.4(2021):778-791.