Nonfiction | Computer & Technology
Large-scale Graph Analysis
by Yingxia Shao 2020-09-17 01:43:44
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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 effic... Read more
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. Less
  • Publication date
  • Language
  • ISBN
  • July 1, 2020
  • eng
  • 9789811539282
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Yingxia Shao
Author
Yingxia Shao is a Research Associate Professor at the School of Computer Science, Beijing University of Posts and Telecommunications. His research interests include large-scale graph analysis, knowled...
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