NUMA-optimized parallel breadth-first search on multicore single-node system

Yuichiro Yasui, Katsuki Fujisawa, Kazushige Goto

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

30 被引用数 (Scopus)

抄録

The breadth-first search (BFS) is one of the most important kernels in graph theory. The Graph500 benchmark measures the performance of any supercomputer performing a BFS in terms of traversed edges per second (TEPS). Previous studies have proposed hybrid approaches that combine a well-known top-down algorithm and an efficient bottom-up algorithm for large frontiers. This reduces some unnecessary searching of outgoing edges in the BFS traversal of a small-world graph, such as a Kronecker graph. In this paper, we describe a highly efficient BFS using column-wise partitioning of the adjacency list while carefully considering the non-uniform memory access (NUMA) architecture. We explicitly manage the way in which each working thread accesses a partial adjacency list in local memory during BFS traversal. Our implementation has achieved a processing rate of 11.15 billion edges per second on a 4-way Intel Xeon E5-4640 system for a scale-26 problem of a Kronecker graph with 2 26 vertices and 230 edges. Not all of the speedup techniques in this paper are limited to the NUMA architecture system. With our winning Green Graph500 submission of June 2013, we achieved 64.12 GTEPS per kilowatt hour on an ASUS Pad TF700T with an NVIDIA Tegra 3 mobile processor.

本文言語英語
ホスト出版物のタイトルProceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
ページ394-402
ページ数9
DOI
出版ステータス出版済み - 2013
外部発表はい
イベント2013 IEEE International Conference on Big Data, Big Data 2013 - Santa Clara, CA, 米国
継続期間: 10 6 201310 9 2013

出版物シリーズ

名前Proceedings - 2013 IEEE International Conference on Big Data, Big Data 2013

その他

その他2013 IEEE International Conference on Big Data, Big Data 2013
国/地域米国
CitySanta Clara, CA
Period10/6/1310/9/13

All Science Journal Classification (ASJC) codes

  • ソフトウェア

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