Large graph computing systems

Chengwen Wu, Guangyan Zhang, Keqin Li, Weimin Zheng

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Large graph computing system is a key tool in big data computing. It can be applied to a variety of big data applications, such as social networks, web page search, and protein interactions. However, the unstructured graph data make data access nonuniform, which poses a great challenge for building an efficient large graph computing system. Fortunately, a lot of large graph computing frameworks have been proposed recently to alleviate the above problems. In general, these frameworks can be categorized into single-node in-memory system, distributed shared memory system, and single-node out-of-core system. Besides, there are some other solutions that utilize flash SSD and GPU to speed up large graph computing. In this chapter, we will reviewthese typical large graph computing systems from a system perspective.

Original languageEnglish
Title of host publicationBig Data Management and Processing
PublisherCRC Press
Pages347-362
Number of pages16
ISBN (Electronic)9781498768085
ISBN (Print)9781498768078
DOIs
Publication statusPublished - 2017 Jan 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

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