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Book synopsis

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.

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik

• Full title: Large-scale Graph Analysis: System, Algorithm and Optimization
• Author: Bin Cui, Lei Chen
• Language: English
• Binding: Paperback
• Number of pages: 146
• EAN: 9789811539305
• ISBN: 9811539308
• ID: 36529297
• Publisher: Springer Verlag, Singapore
• Weight: 256 g
• Dimensions: 235 × 155 × 9 mm
• Date of publishing: 02. July 2021

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