SCCMulti An Improved Parallel Strongly Connected Components Algorithm Academic Article uri icon

abstract

  • Tarjan's famous linear time, sequential algorithm for finding the strongly connected components (SCCs) of a graph relies on depth first search, which is inherently sequential. Deterministic parallel algorithms solve this problem in logarithmic time using matrix multiplication techniques, but matrix multiplication requires a large amount of total work. Randomized algorithms based on reachability - the ability to get from one vertex to another along a directed path - greatly improve the work bound in the average case. However, these algorithms do not always perform well; for instance, Divide-and-Conquer Strong Components (DCSC), a scalable, divide-and-conquer algorithm, has good expected theoretical limits, but can perform very poorly on graphs for which the maximum reachability of any vertex is small. A related algorithm, MultiPivot, gives very high probability guarantees on the total amount of work for all graphs, but this improvement introduces an overhead that increases the average running time. This work introduces SCCMulti, a multi-pivot improvement of DCSC that offers the same consistency as MultiPivot without the time overhead. We provide experimental results demonstrating SCCMulti's scalability; these results also show that SCCMulti is more consistent than DCSC and is always faster than MultiPivot.

published proceedings

  • PPOPP'14: PROCEEDINGS OF THE 2014 ACM SIGPLAN SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING

author list (cited authors)

  • Tomkins, D., Smith, T., Amato, N. M., Rauchwerger, L., & Machinery, A. C.

citation count

  • 1

complete list of authors

  • Tomkins, Daniel||Smith, Timmie||Amato, Nancy M||Rauchwerger, Lawrence||Machinery, Assoc Comp

editor list (cited editors)

  • Moreira, J. E., & Larus, J. R.

publication date

  • January 2014