CuSP: A Customizable Streaming Edge Partitioner for Distributed Graph Analytics

Graph analytics systems must analyze graphs with billions of vertices and edges which require several terabytes of storage. Distributed-memory clusters are often used for analyzing such large graphs since the main memory of a single machine is usually restricted to a few hundreds of gigabytes. This...

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Vydané v:	Proceedings - IEEE International Parallel and Distributed Processing Symposium s. 439 - 450
Hlavní autori:	Hoang, Loc, Dathathri, Roshan, Gill, Gurbinder, Pingali, Keshav
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.05.2019
Predmet:	Clustering algorithms distributed-memory computing graph analytics graph partitioning Heuristic algorithms Microsoft Windows Mirrors Parallel processing Partitioning algorithms streaming partitioners Two dimensional displays
ISSN:	1530-2075
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