DistTC:高性能分布式三角形计数

2019 IEEE High Performance Extreme Computing Conference (HPEC) Pub Date : 2019-09-01 DOI:10.1109/HPEC.2019.8916438

Loc Hoang, Vishwesh Jatala, Xuhao Chen, U. Agarwal, Roshan Dathathri, G. Gill, K. Pingali

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引用次数: 25

摘要

我们描述了一种新的多机器多gpu的三角形计数实现，它利用了一种新的应用程序无关的图分区策略，消除了三角形计数期间几乎所有的主机间通信。实验结果表明，这种分布式三角形计数实现可以处理非常大的图，如clueweb12，它有近10亿个顶点和370亿个边，比2018年图形挑战赛冠军TriCore的速度快1.6倍。

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DistTC: High Performance Distributed Triangle Counting

We describe a novel multi-machine multi-GPU implementation of triangle counting which exploits a novel application-agnostic graph partitioning strategy that eliminates almost all inter-host communication during triangle counting. Experimental results show that this distributed triangle counting implementation can handle very large graphs such as clueweb12, which has almost one billion vertices and 37 billion edges, and it is up to 1.6× faster than TriCore, the 2018 Graph Challenge champion.

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来源期刊

2019 IEEE High Performance Extreme Computing Conference (HPEC)

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