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...

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Detalles Bibliográficos

Publicado en:	Communications of the ACM Vol. 59; no. 5; pp. 78 - 88
Autores principales:	LENHARTH, ANDREW, NGUYEN, DONALD, PINGALI, KESHAV
Formato:	Artículo
Publicado:	Association for Computing Machinery May2016
Materias:	Planar graphs Random graphs Algorithms Electronic data processing Graph theory
Acceso en línea:	Ver este registro en EBSCOhost