A computational study of external-memory BFS algorithms


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 (<i>minutes</i> as compared to <i>hours</i>) than internal-memory BFS, even if more than half of the input resides internally.

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@inproceedings{Ajwani2006ACS, title={A computational study of external-memory BFS algorithms}, author={Deepak Ajwani and Roman Dementiev and Ulrich Meyer}, booktitle={SODA}, year={2006} }