On Batcher's merge sorts as parallel sorting algorithms

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Abstract

We examine the average running times of Batcher's bitonic merge and Batcher's odd-even merge when they are used as parallel merging algorithms. It has been shown previously that the running time of odd-even merge can be upper bounded by a function of the maximal rank difference for elements in the two input sequences. Here we give an almost matching lower bound for odd-even merge as well as a similar upper bound for (a special version of) bitonic merge. From this follows that the average running time of odd-even merge (bitonic merge) is Θ((n/p)(1+log(1+p2/n))) (O((n/p)(1+log(1+p2/n))), resp.) where n is the size of the input and p is the number of processors. Using these results we then show that the average running times of odd-even merge sort and bitonic merge sort are O((n/p) (log n + (log(1 +p2/n)) 2)), that is, the two algorithms are optimal on the average if n ≥ p2/2√log p. © 1998 Springer-Verlag.

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APA

Rüb, C. (1998). On Batcher’s merge sorts as parallel sorting algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1373 LNCS, pp. 410–420). https://doi.org/10.1007/BFb0028577

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