See applications run and throughput jump: The case for redundant computing in HPC

R. Riesen, Kurt B. Ferreira, Jon Stearley
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引用次数: 26

Abstract

For future parallel-computing systems with as few as twenty-thousand nodes we propose redundant computing to reduce the number of application interrupts. The frequency of faults in exascale systems will be so high that traditional checkpoint/restart methods will break down. Applications will experience interruptions so often that they will spend more time restarting and recovering lost work, than computing the solution. We show that redundant computation at large scale can be cost effective and allows applications to complete their work in significantly less wall-clock time. On truly large systems, redundant computing can increase system throughput by an order of magnitude.
请参阅应用程序运行和吞吐量跳转:HPC中冗余计算的情况
对于未来只有2万个节点的并行计算系统,我们建议采用冗余计算来减少应用程序中断的数量。百亿亿级系统中的故障频率将如此之高,以至于传统的检查点/重启方法将失效。应用程序将经常遇到中断,因此它们将花费更多的时间重新启动和恢复丢失的工作,而不是计算解决方案。我们表明,大规模的冗余计算可以具有成本效益,并允许应用程序在更短的时间内完成工作。在真正的大型系统上,冗余计算可以将系统吞吐量提高一个数量级。
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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