A computational study of external-memory BFS algorithms

  • Authors:
  • Deepak Ajwani;Roman Dementiev;Ulrich Meyer

  • Affiliations:
  • Max-Planck-Institut für Informatik, Saarbrücken, Germany;University Karlsruhe, Karlsruhe, Germany;Max-Planck-Institut für Informatik, Saarbrücken, Germany

  • Venue:
  • SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
  • Year:
  • 2006

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Abstract

Breadth First Search (BFS) traversal is an archetype for many important graph problems. However, computing a BFS level decomposition for massive graphs was considered nonviable so far, because of the large number of I/Os it incurs. This paper presents the first experimental evaluation of recent external-memory BFS algorithms for general graphs. With our STXXL based implementations exploiting pipelining and disk-parallelism, we were able to compute the BFS level decomposition of a web-crawl based graph of around 130 million nodes and 1.4 billion edges in less than 4 hours using single disk and 2.3 hours using 4 disks. We demonstrate that some rather simple external-memory algorithms perform significantly better (minutes as compared to hours) than internal-memory BFS, even if more than half of the input resides internally.