DocumentCode :
659595
Title :
Approximate triangle counting algorithms on multi-cores
Author :
Rahman, Mosaddequr ; Al Hasan, Mohammad
Author_Institution :
Dept. of Comput. & Inf. Sci., Indiana Univ.-Purdue Univ., Indianapolis, IN, USA
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
127
Lastpage :
133
Abstract :
Counting triangles in a large network is an important research task because of its usages in analyzing large networks. However, this task becomes expensive when runs on large networks with millions of nodes and millions of edges. For efficient triangle counting on such networks, researchers in recent years have adopted approximate counting or have proposed parallel or distributed solutions. In this work, we propose an approximate triangle counting algorithm, that runs on multi-core computers through a multi-threaded implementation. We show that for a given speedup factor, our method has a better approximation accuracy; further, the multi-threaded implementation that we propose is much superior to the Hadoop based distributed methods that earlier algorithms propose.
Keywords :
approximation theory; multi-threading; multiprocessing systems; parallel algorithms; Hadoop based distributed methods; approximate counting; approximate triangle counting algorithm; approximation accuracy; distributed solution; large networks; multicore computers; multicores; multithreaded implementation; parallel solution; speedup factor; triangle counting algorithms; Accuracy; Approximation algorithms; Approximation methods; Electronic publishing; Encyclopedias; Instruction sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/BigData.2013.6691744
Filename :
6691744
Link To Document :
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