Parallel Graph Analytics.
The article explains data-centric abstractions and execution strategies to exploit parallelism in large-scale graph analytics. It describes the categories of graphs including planar graphs, social network graphs and random graphs and illustrates the concepts of data-centric abstraction of algorithms...
| Publicado en: | Communications of the ACM Vol. 59; no. 5; pp. 78 - 88 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Association for Computing Machinery
May2016
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=115178365&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 115178365 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: May2016 vid: 59 iid: 5 pid: 68 pub: Association for Computing Machinery artinfo: ui: 115178365 10.1145/2901919 ppf: 78 ppct: 10 formats: tig: atl: Parallel Graph Analytics. aug: au: LENHARTH, ANDREW NGUYEN, DONALD PINGALI, KESHAV affil: Research associate in the Institute for Computational Engineering and Sciences Lecturer in the Department of Computer Science at the University of Texas at Austin Senior developer in Synthace Ltd., London, U.K Ph.D. from the University of Texas at Austin "Tex" Moncrief Chair of Grid and Distributed Computing Professor in the Department of Computer Science at the University of Texas at Austin Professor in the Institute for Computational Engineering and Sciences at the University of Texas at Austin su: Planar graphs Random graphs Algorithms Electronic data processing Graph theory sug: subj: Planar graphs Random graphs Algorithms Electronic data processing Graph theory ab: The article explains data-centric abstractions and execution strategies to exploit parallelism in large-scale graph analytics. It describes the categories of graphs including planar graphs, social network graphs and random graphs and illustrates the concepts of data-centric abstraction of algorithms using the Dijkstra and Bellman-Ford algorithms for the singe-source shortest path problem and collaborative filtering. It outlines vital choices in implementing parallel graph analytics programs. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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