Large-scale Graph Analysis: System, Algorithm and Optimization
Produktnummer:
1806d2b45d94ce46f49d86f5c56510de60
| Autor: | Chen, Lei Cui, Bin Shao, Yingxia |
|---|---|
| Themengebiete: | Cohesive subgraph detection Distributed graph computing Graph algorithm optimization Graph matching Graph partition-aware system Large-scale graph analysis Parallel graph computing Subgraph enumeration |
| Veröffentlichungsdatum: | 02.07.2020 |
| EAN: | 9789811539275 |
| Sprache: | Englisch |
| Seitenzahl: | 146 |
| Produktart: | Gebunden |
| Verlag: | Springer Singapore |
Produktinformationen "Large-scale Graph Analysis: System, Algorithm and Optimization"
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.
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