Large-scale Graph Analysis: System, Algorithm and Optimization

Lei Chen, Bin Cui, Yingxia Shao, et al.

PDF
ca. 139,09
Amazon iTunes Thalia.de Weltbild.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Springer Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

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.

Weitere Titel in dieser Kategorie

Kundenbewertungen

Schlagwörter

Graph algorithm optimization, Distributed graph computing, Graph partition-aware system, Large-scale graph analysis, Subgraph enumeration, Cohesive subgraph detection, Graph matching, Parallel graph computing