Optimal scheduling of in-situ analysis for large-scale scientific simulations
Optimal scheduling of in-situ analysis for large-scale scientific simulations
复制标题
大规模科学模拟现场分析的优化调度
DOI：
10.1145/2807591.2807656
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
M. Papka
中科院分区：
文献类型：
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作者：
Preeti Malakar;V. Vishwanath;T. Munson;Christopher Knight;M. Hereld;S. Leyffer;M. Papka
当今的领导力计算设施使在前所未有的量表上执行变革性模拟。但是，分析这些模拟的大量产出仍然是一个挑战。该输出的大多数分析是在模拟末尾以后处理模式进行的。由于I/O带宽较差，读取分析输出的时间可能会显着高，这增加了端到端的仿真分析时间。仿真时间分析可以减少此端到端时间。在这项工作中，我们介绍了原位分析作为数值优化问题的计划，以最大程度地提高受资源约束（例如I/O带宽，网络带宽，计算速率和可用内存）等资源约束的在线分析数量。我们通过对IBM Blue Gene/Q系统的两项应用程序案例研究证明了方法的有效性。
Today's leadership computing facilities have enabled the execution of transformative simulations at unprecedented scales. However, analyzing the huge amount of output from these simulations remains a challenge. Most analyses of this output is performed in post-processing mode at the end of the simulation. The time to read the output for the analysis can be significantly high due to poor I/O bandwidth, which increases the end-to-end simulation-analysis time. Simulation-time analysis can reduce this end-to-end time. In this work, we present the scheduling of in-situ analysis as a numerical optimization problem to maximize the number of online analyses subject to resource constraints such as I/O bandwidth, network bandwidth, rate of computation and available memory. We demonstrate the effectiveness of our approach through two application case studies on the IBM Blue Gene/Q system.