In this paper we present efficient algorithms for sorting on the Parallel Disks Model (PDM). Numerous asymptotically optimal algorithms have been proposed in the literature. However many of these merge based algorithms have large underlying constants in the time bounds, because they suffer from the lack of read parallelism on PDM. The irregular consumption of the runs during the merge affects the read parallelism and contributes to the increased sorting time. In this paper we first introduce a novel idea called the dirty sequence accumulation that improves the read parallelism. Secondly, we show analytically that this idea can reduce the number of parallel I/O's required to sort the input close to the lower bound of [Formula: see text]. We experimentally verify our dirty sequence idea with the standard R-Way merge and show that our idea can reduce the number of parallel I/Os to sort on PDM significantly.

中文翻译：

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并行磁盘模型的高效核外排序算法。

在本文中，我们提出了在并行磁盘模型 (PDM) 上进行排序的有效算法。文献中已经提出了许多渐近最优算法。然而，许多这些基于合并的算法在时间范围内都有很大的底层常量，因为它们缺乏 PDM 上的读取并行性。合并期间运行的不规则消耗会影响读取并行度并导致排序时间增加。在本文中，我们首先介绍了一种称为脏序列累积的新想法，它提高了读取并行性。其次，我们分析表明，这个想法可以减少对接近 [公式：见正文] 下界的输入进行排序所需的并行 I/O 的数量。