书目名称 | Large-scale Graph Analysis: System, Algorithm and Optimization | 编辑 | Yingxia Shao,Bin Cui,Lei Chen | 视频video | | 概述 | Shares techniques for optimizing large-scale graph algorithms in distributed settings.Introduces three optimized graph analysis algorithms (i.e., subgraph enumeration, subgraph detection and graph ext | 丛书名称 | Big Data Management | 图书封面 |  | 描述 | .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.. | 出版日期 | Book 2020 | 关键词 | Large-scale graph analysis; Graph algorithm optimization; Distributed graph computing; Parallel graph c | 版次 | 1 | doi | https://doi.org/10.1007/978-981-15-3928-2 | isbn_softcover | 978-981-15-3930-5 | isbn_ebook | 978-981-15-3928-2Series ISSN 2522-0179 Series E-ISSN 2522-0187 | issn_series | 2522-0179 | copyright | Springer Nature Singapore Pte Ltd. 2020 |
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