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Tight bounds for prefetching and buffer management algorithms for parallel I/O systems

机译:并行I / O系统的预取和缓冲区管理算法的严格界限

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The I/O performance of applications in multiple-disk systems can be improved by overlapping disk accesses. This requires the use of appropriate prefetching and buffer management algorithms that ensure the most useful blocks are accessed and retained in the buffer. In this paper, we answer several fundamental questions on prefetching and buffer management for distributed-buffer parallel I/O systems. First, we derive and prove the optimality of an algorithm, P-min, that minimizes the number of parallel I/Os. Second, we analyze P-con, an algorithm that always matches its replacement decisions with those of the well-known demand-paged MIN algorithm. We show that P-con can become fully sequential in the worst case. Third, we investigate the behavior of on-line algorithms for multiple-disk prefetching and buffer management. We define and analyze P-Iru, a parallel version of the traditional LRU buffer management algorithm. Unexpectedly, we find that the competitive ratio of P-Iru is independent of the number of disks. Finally, we present the practical performance of these algorithms on randomly generated reference strings. These results confirm the conclusions derived from the analysis on worst case inputs.
机译:通过重叠磁盘访问,可以提高多磁盘系统中应用程序的I / O性能。这要求使用适当的预取和缓冲区管理算法,以确保访问最有用的块并将其保留在缓冲区中。在本文中,我们回答了有关分布式缓冲区并行I / O系统的预取和缓冲区管理的几个基本问​​题。首先,我们推导并证明了最小化并行I / O数量的算法P-min的最优性。其次,我们分析P-con,该算法始终将其替换决策与众所周知的按需分配MIN算法的决策相匹配。我们表明,在最坏的情况下,P-con可能会变得完全顺序。第三,我们研究了用于多磁盘预取和缓冲区管理的在线算法的行为。我们定义和分析P-Iru,它是传统LRU缓冲区管理算法的并行版本。出乎意料的是,我们发现P-Iru的竞争比率与磁盘数量无关。最后,我们介绍了这些算法在随机生成的参考字符串上的实际性能。这些结果证实了对最坏情况输入的分析得出的结论。

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