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

Fingerprint

Computer systems
Data storage equipment
Websites
Proteins
Big data
Graph
Graphics processing unit
Node

All Science Journal Classification (ASJC) codes

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

Cite this

Wu, C., Zhang, G., Li, K., & Zheng, W. (2017). Large graph computing systems. In Big Data Management and Processing (pp. 347-362). CRC Press. https://doi.org/10.1201/9781315154008
Wu, Chengwen ; Zhang, Guangyan ; Li, Keqin ; Zheng, Weimin. / Large graph computing systems. Big Data Management and Processing. CRC Press, 2017. pp. 347-362
@inbook{dd6e906ae40c4544b55387e48bacb442,
title = "Large graph computing systems",
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.",
author = "Chengwen Wu and Guangyan Zhang and Keqin Li and Weimin Zheng",
year = "2017",
month = "1",
day = "1",
doi = "10.1201/9781315154008",
language = "English",
isbn = "9781498768078",
pages = "347--362",
booktitle = "Big Data Management and Processing",
publisher = "CRC Press",

}

Wu, C, Zhang, G, Li, K & Zheng, W 2017, Large graph computing systems. in Big Data Management and Processing. CRC Press, pp. 347-362. https://doi.org/10.1201/9781315154008

Large graph computing systems. / Wu, Chengwen; Zhang, Guangyan; Li, Keqin; Zheng, Weimin.

Big Data Management and Processing. CRC Press, 2017. p. 347-362.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Large graph computing systems

AU - Wu, Chengwen

AU - Zhang, Guangyan

AU - Li, Keqin

AU - Zheng, Weimin

PY - 2017/1/1

Y1 - 2017/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85052592857&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052592857&partnerID=8YFLogxK

U2 - 10.1201/9781315154008

DO - 10.1201/9781315154008

M3 - Chapter

AN - SCOPUS:85052592857

SN - 9781498768078

SP - 347

EP - 362

BT - Big Data Management and Processing

PB - CRC Press

ER -

Wu C, Zhang G, Li K, Zheng W. Large graph computing systems. In Big Data Management and Processing. CRC Press. 2017. p. 347-362 https://doi.org/10.1201/9781315154008