Abstract
There are very few parallel programming paradigms that consistently produce fast parallel algorithms. Divide-and-conquer is the one notable exception. The most common approach to parallel algorithm development is to try and parallelize existing sequential algorithms. The goal of this paper is to further our understanding about why some sequential algorithms parallelize better than others. We study the maximum acyclic subgraph problem and several closely related sequential approximation algorithms for it. The standard parallelization approach is applied to the sequential algorithms and vastly different parallel complexities are obtained for the resultant algorithms. That is, some of our parallel algorithms run in NC, whereas decisions problems based on others turn but to be P-complete. We find the contrasting nature of these results interesting.
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