Large-scale Graph Analysis: System, Algorithm and Optimization

Large-scale Graph Analysis: System, Algorithm and Optimization

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This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph…

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Title Statements

  • Full title :Large-scale Graph Analysis: System, Algorithm and Optimization / by Yingxia Shao, Bin Cui, Lei Chen.

Summary

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms - the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.

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Edition Statements

  • Publication Date:2020 ;
  • Edition:1st ed. 2020

Publication Statements

The Physical Object

  • Description:XIII, 146 p. 78 illus., 30 illus. in color. : online resource.

Edition Identifiers

  • ISBN:9789811539282, 9811539286, 9811539278, 9789811539275
  • oclc:on1201294449
  • LC Classification:QA76.9.B45
  • Dewey Decimal:005.7

Table of Contents

1. Introduction -- 2. Graph Computing Systems for Large-Scale Graph Analysis -- 3. Partition-Aware Graph Computing System -- 4. Efficient Parallel Subgraph Enumeration -- 5. Efficient Parallel Graph Extraction -- 6. Efficient Parallel Cohesive Subgraph Detection -- 7. Conclusions.

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Subjects

Big data Computer Science Data Mining data processing Données volumineuses Electronic Data Processing Exploration de données (Informatique) graph algorithms Informatique Management information systems physics Physique Systèmes d'information de gestion

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