Coarse Grained Parallel Selection

L. Boxer
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Abstract

We analyze the running time of the Saukas-Song algorithm for selection on a coarse grained multicomputer without expressing the running time in terms of communication rounds. This shows that while in the best case the Saukas-Song algorithm runs in asymptotically optimal time, in general it does not. We propose other algorithms for coarse grained selection that have optimal expected running time.
粗粒度并行选择
我们在不以通信轮数表示运行时间的情况下,分析了Saukas-Song算法在粗粒度多计算机上进行选择的运行时间。这表明,虽然在最佳情况下,Saukas-Song算法在渐近最优时间内运行,但通常情况下它不会。我们提出了其他具有最佳预期运行时间的粗粒度选择算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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