
doi: 10.1007/bfb0015428
handle: 11858/00-001M-0000-0014-ACA1-8
We develop an arsenal of tools for improving the efficiency of parallel algorithms for network-flow problems and apply it to a maximum-flow algorithm of Goldberg, a blocking-flow algorithm of Shiloach and Vishkin, and a maximum-flow algorithm of Ahuja and Orlin. Depending on the exact model of computation and the time available for the computation, we achieve a polylogarithmic reduction in the time-processor product. In particular, this leads to the first parallel implementations with optimal speedup of the corresponding sequential algorithms.
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