Performance Evaluation of Supercomputer Fugaku using Breadth-First Search Benchmark in Graph500

Masahiro Nakao, Koji Ueno, Katsuki Fujisawa, Yuetsu Kodama, Mitsuhisa Sato

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

2 被引用数 (Scopus)

抄録

There is increasing demand for the high-speed processing of large-scale graphs in various fields. However, such graph processing requires irregular calculations, making it difficult to scale performance on large-scale distributed memory systems. Against this background, Graph500, a competition for evaluating the performance of large-scale graph processing, has been held. We developed breadth-first search (BFS), which is one of the benchmark kernels used in Graph500, and took the top spot a total of 10 times using the K computer. In this paper, we tune BFS performance and evaluate it using the supercomputer Fugaku, which is the successor to the K computer. The results of evaluating BFS for a large-scale graph composed of about 1.1 trillion vertices and 17.6 trillion edges using 92,160 nodes of Fugaku indicate that Fugaku has 2.27 times the performance of the K computer. Fugaku took the top spot on Graph500 in June 2020.

本文言語英語
ホスト出版物のタイトルProceedings - 2020 IEEE International Conference on Cluster Computing, CLUSTER 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ408-409
ページ数2
ISBN(電子版)9781728166773
DOI
出版ステータス出版済み - 9 2020
イベント22nd IEEE International Conference on Cluster Computing, CLUSTER 2020 - Kobe, 日本
継続期間: 9 14 20209 17 2020

出版物シリーズ

名前Proceedings - IEEE International Conference on Cluster Computing, ICCC
2020-September
ISSN(印刷版)1552-5244

会議

会議22nd IEEE International Conference on Cluster Computing, CLUSTER 2020
国/地域日本
CityKobe
Period9/14/209/17/20

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • ハードウェアとアーキテクチャ
  • 信号処理

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