大規模グラフ解析<br>Large-scale Graph Analysis: System, Algorithm and Optimization

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  • 電子書籍

大規模グラフ解析
Large-scale Graph Analysis: System, Algorithm and Optimization

  • 著者名:Shao, Yingxia/Cui, Bin/Chen, Lei
  • 価格 ¥26,639 (本体¥24,218)
  • Springer(2020/07/01発売)
  • ポイント 242pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9789811539275
  • eISBN:9789811539282

ファイル: /

Description

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 fordesigning efficient large-scale graph algorithms.

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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