Survey of external memory large-scale graph processing on a multi-core system

被引:4
作者
Huang, Jianqiang [1 ,2 ]
Qin, Wei [1 ]
Wang, Xiaoying [2 ]
Chen, Wenguang [1 ,2 ]
机构
[1] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
[2] Qinghai Univ, Dept Comp Technol & Applicat, Xining 810016, Qinghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Graph data processing; Parallel computing; Computing model; Graph algorithms; FRAMEWORK; GPU; ALGORITHMS; MODEL;
D O I
10.1007/s11227-019-03023-0
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The fast development of big data computing contributes to the fact that large-scale graph processing has become a basic computing model in both academic and industrial communities, and it has been applied in many actual big data computing works, such as social network analysis, Web search, and product promotion. These computing works include large-scale graphs of billions of vertices and trillions of edges. Such scale has brought many challenges to large-scale graph processing. This paper mainly introduces the essential features and challenges of large-scale graph processing and how we can handle billions of edges on a multi-core machine, for which we represent out-of-core processing system and semi-external memory processing systems. This paper also summarizes the key technologies in graph processing systems and forecasts the future development of large-scale graph processing systems.
引用
收藏
页码:549 / 579
页数:31
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