A Novel Metric to Evaluate In Situ Workflows

A Novel Metric to Evaluate In Situ Workflows
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DOI:
10.1007/978-3-030-50371-0_40
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发表时间:
2020-05-26
期刊:
Computational Science – ICCS 2020
影响因子:
--
通讯作者:
Deelman E
Deelman E
中科院分区:
其他
文献类型:
--
作者:
Do TM;Pottier L;Thomas S;da Silva RF;Cuendet MA;Weinstein H;Estrada T;Taufer M;Deelman E

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性能评估对于理解科学工作流的行为和高效利用高性能计算架构上的资源至关重要。在这项研究中,我们的目标是一种新兴的工作流类型,称为原位工作流。通过对现场工作流最新研究的分析,我们建立了一个理论框架模型,帮助描述这种工作流。我们进一步提出了一个轻量级的度量来评估就地工作流执行的资源使用效率。通过将此指标应用于简单但具有代表性的合成工作流,我们探索了两种可能的场景(Idle Simulation和Idle Analyzer),以执行实际的现场工作流。实验结果表明,在我们的目标系统上,传输放置(专用节点上的分析)和helper-core配置(分析与仿真共同分配)的性能没有实质性差异。
Performance evaluation is crucial to understanding the behavior of scientific workflows and efficiently utilizing resources on high-performance computing architectures. In this study, we target an emerging type of workflow, called in situ workflows. Through an analysis of the state-of-the-art research on in situ workflows, we model a theoretical framework that helps characterize such workflows. We further propose a lightweight metric for assessing resource usage efficiency of an in situ workflow execution. By applying this metric to a simple, yet representative, synthetic workflow, we explore two possible scenarios (Idle Simulation and Idle Analyzer) for the execution of real in situ workflows. Experimental results show that there is no substantial difference in the performance of both the in transit placement (analytics on dedicated nodes) and the helper-core configuration (analytics co-allocated with simulation) on our target system.
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