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Large-scale Graph Analysis: System, Algorithm and Optimization

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Artikelnr: SK0210958-SE20260527-055838 Kategori: Etikett:

Beskrivning

Beskrivning

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.

Om boken

Om denna bok

Large-scale Graph Analysis: System, Algorithm and Optimization av Yingxia Shao och Bin Cui är en Inbunden bok med 146 sidor på Engelska. Detta är den 1:a upplagan som utgavs 2020 av Springer Nature.

Produktinformation

Kategori
Okänd
Bandtyp
Inbunden
Språk
Engelska
ISBN
9789811539275
Upplaga
1
Utgiven
2020-07-02
Förlag
Springer Nature
Sidantal
146