Algorithms for high-throughput disk-to-disk sorting

H. Sundar, D. Malhotra, K. Schulz
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引用次数: 8

Abstract

In this paper, we present a new out-of-core sort algorithm, designed for problems that are too large to fit into the aggregate RAM available on modern supercomputers. We analyze the performance including the cost of IO and demonstrate the fastest (to the best of our knowledge) reported throughput using the canonical sortBenchmark on a general-purpose, production HPC resource running Lustre. By clever use of available storage and a formulation of asynchronous data transfer mechanisms, we are able to almost completely hide the computation (sorting) behind the IO latency. This latency hiding enables us to achieve comparable execution times, including the additional temporary IO required, between a large sort problem (5TB) run as a single, in-RAM sort and our out-of-core approach using 1/10th the amount of RAM. In our largest run, sorting 100TB of records using 1792 hosts, we achieved an end-to-end throughput of 1.24TB/min using our general-purpose sorter, improving on the current Daytona record holder by 65%.
高吞吐量磁盘到磁盘排序算法
在本文中,我们提出了一种新的核外排序算法,该算法是为现代超级计算机上的总内存无法容纳的问题而设计的。我们分析了性能,包括IO成本,并在运行Lustre的通用生产HPC资源上使用规范的sortBenchmark演示了最快(据我们所知)报告的吞吐量。通过巧妙地使用可用存储和异步数据传输机制的公式,我们能够几乎完全隐藏IO延迟背后的计算(排序)。这种延迟隐藏使我们能够实现可比较的执行时间,包括所需的额外临时IO,在大型排序问题(5TB)作为单个RAM内排序和我们的外核方法之间运行,使用1/10的RAM量。在我们最大的一次运行中,使用1792台主机对100TB的记录进行排序,使用我们的通用排序器实现了1.24TB/min的端到端吞吐量,比当前的Daytona记录保持者提高了65%。
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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