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Output-sensitive algorithms for optimally constructing the upper envelope of straight line segments in parallel

机译:输出敏感算法,用于最佳地并行构造直线段的上包络

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The importance of the sensitivity of an algorithm to the output size of a problem is well-known especially if the upper bound on the output size is known to be not too large. In this paper we focus on the problem of designing very fast parallel algorithms for constructing the upper envelope of straight-line segments that achieve the O (n log H) work-bound for input size n and output size H. When the output size is small, our algorithms run faster than the algorithms whose running times are sensitive only to the input size. Since the upper bound on the output size of the upper envelop problem is known to be small (nα(n)), where α(n) is a slowly growing inverse-Ackerman's function, the algorithms are no worse in cost than the previous algorithms in the worst case of the output size. Our algorithms are designed for the arbitrary CRCW PRAM model. We first describe an O (log n·(log H + log log n)) time deterministic algorithm for the problem, that achieves O (n log H) work bound for H = Ω(log n). We then present a fast randomized algorithm that runs in expected time O(log H·log log n) with high probability and does O(n log H) work. For log H = Ω(log log n), we can achieve the running time of O(log H) while simultaneously keeping the work optimal. We also present a fast randomized algorithm that runs in O(log n/log k) time with nk processors, k > log~(Ω(1)) n. The algorithms do not assume any prior input distribution and the running times hold with high probability.
机译:算法敏感性对问题的输出大小的重要性是众所周知的,特别是如果已知输出大小的上限不太大的话。在本文中,我们关注于设计非常快速的并行算法来构造直线段的上包络的问题,这些直线段对于输入大小n和输出大小H实现O(n log H)的工作范围。较小,我们的算法比运行时间仅对输入大小敏感的算法运行得更快。由于已知上信封问题的输出大小的上限很小(nα(n)),其中α(n)是一个缓慢增长的逆阿克曼函数,因此该算法的成本不会比以前的算法差在输出大小最坏的情况下。我们的算法是为任意CRCW PRAM模型设计的。我们首先针对该问题描述一种O(log n·(log H + log log n))时间确定性算法,该算法可实现H =Ω(log n)的O(n log H)功。然后,我们提出一种快速随机算法,该算法以较高的概率在预期时间O(log H·log log n)中运行,并且O(n log H)起作用。对于log H =Ω(log log n),我们可以达到O(log H)的运行时间,同时保持最佳工作状态。我们还提出了一种快速随机算法,该算法使用nk个处理器在O(log n / log k)时间内运行,k> log〜(Ω(1))n。该算法不假定任何先前的输入分布,并且运行时间具有很高的概率。

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