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An experimental study of scheduling algorithms for many-task applications

机译:用于多任务应用的调度算法的实验研究

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The paper studies the performance of algorithms for scheduling of many-task applications in distributed computing systems. Two important classes of such applications are considered: bags-of-tasks and workflows. The comparison of algorithms is performed on the basis of discrete-event simulation for various application cases and system configurations. The developed simulation framework based on SimGrid toolkit provides the necessary tools for implementation of scheduling algorithms, generation of synthetic systems and applications, execution of simulation experiments and analysis of results. This allowed to perform a large number of experiments in a reasonable amount of time and to ensure reproducible results. The conducted experiments demonstrate the dependence of the performance of studied algorithms on various application and system characteristics. While confirming the performance advantage of advanced static algorithms, the presented results reveal some interesting insights. In particular, the accuracy of the used network model helped to demonstrate the limitations of simple analytical models for scheduling of data-intensive parallel applications with static algorithms.
机译:本文研究了分布式计算系统中用于调度多任务应用程序的算法的性能。考虑了此类应用程序的两个重要类别:任务包和工作流。在各种应用案例和系统配置的离散事件模拟的基础上,对算法进行比较。基于SimGrid工具箱开发的仿真框架为实现调度算法,生成综合系统和应用程序,执行仿真实验以及结果分析提供了必要的工具。这样可以在合理的时间内执行大量实验,并确保可重复的结果。进行的实验证明了所研究算法的性能对各种应用程序和系统特性的依赖性。在确认了高级静态算法的性能优势的同时,给出的结果揭示了一些有趣的见解。特别是,所用网络模型的准确性有助于说明简单分析模型在使用静态算法调度数据密集型并行应用程序时的局限性。

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