Vai al contenuto principale della pagina
Autore: | Shao Yingxia |
Titolo: | Large-scale Graph Analysis: System, Algorithm and Optimization [[electronic resource] /] / by Yingxia Shao, Bin Cui, Lei Chen |
Pubblicazione: | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
Edizione: | 1st ed. 2020. |
Descrizione fisica: | 1 online resource (XIII, 146 p. 78 illus., 30 illus. in color.) |
Disciplina: | 511.5 |
Soggetto topico: | Big data |
Data mining | |
Physics | |
Management information systems | |
Computer science | |
Big Data | |
Data Mining and Knowledge Discovery | |
Applications of Graph Theory and Complex Networks | |
Management of Computing and Information Systems | |
Persona (resp. second.): | CuiBin |
ChenLei | |
Nota di bibliografia: | Includes bibliographical references. |
Nota di contenuto: | 1. Introduction -- 2. Graph Computing Systems for Large-Scale Graph Analysis -- 3. Partition-Aware Graph Computing System -- 4. Efficient Parallel Subgraph Enumeration -- 5. Efficient Parallel Graph Extraction -- 6. Efficient Parallel Cohesive Subgraph Detection -- 7. Conclusions. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Large-scale Graph Analysis: System, Algorithm and Optimization |
ISBN: | 981-15-3928-6 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996465444003316 |
Lo trovi qui: | Univ. di Salerno |
Opac: | Controlla la disponibilità qui |