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首页> 外文期刊>Computing and informatics >LOGOS: ENABLING LOCAL RESOURCE MANAGERS FOR THE EFFICIENT SUPPORT OF DATA-INTENSIVE WORKFLOWS WITHIN GRID SITES
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LOGOS: ENABLING LOCAL RESOURCE MANAGERS FOR THE EFFICIENT SUPPORT OF DATA-INTENSIVE WORKFLOWS WITHIN GRID SITES

机译:徽标:启用本地资源管理器以在网格站点内有效地支持数据密集型工作流

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摘要

In this study we discuss how to enable grid sites for the support of data-intensive workflows. Usually, within grid sites, tasks and resources are administrated by local resource managers (LRMs). Many of LRMs have been designed for managing compute-intensive applications. Therefore, data-intensive workflow applications might not perform well on such environments due to the number and size of data transfers between tasks. To improve the performance of such kind of applications it is necessary to redefine the scheduling policies integrated on LRMs. This paper proposes a novel scheme for efficiently supporting data-intensive workflows in LRMs within grid sites. Such scheme is partially implemented in our grid middleware LOGOS and used to improve the performance of a well known LRM: HTCondor. The core of LOGOS is a novel communication-aware scheduling algorithm (PPSA) capable of finding near-optimal solutions. Experiments conducted in this study showed that our approach leads to performance improvements up to 52 % in the management of data-intensive workflow applications.
机译:在本研究中,我们讨论如何启用网格站点以支持数据密集型工作流。通常,在网格站点内,任务和资源由本地资源管理器(LRM)管理。许多LRM设计用于管理计算密集型应用程序。因此,由于任务之间数据传输的数量和大小,数据密集型工作流应用程序在此类环境中可能无法很好地执行。为了提高此类应用程序的性能,有必要重新定义集成在LRM上的调度策略。本文提出了一种有效支持网格站点内LRM中数据密集型工作流的新颖方案。这种方案已在我们的网格中间件LOGOS中部分实现,并用于提高著名的LRM:HTCondor的性能。 LOGOS的核心是一种新颖的通信感知调度算法(PPSA),它能够找到接近最佳的解决方案。在这项研究中进行的实验表明,我们的方法可以将数据密集型工作流应用程序的管理性能提高52%。

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