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Performance Analysis of Grid DAG Scheduling Algorithms using MONARC Simulation Tool

机译:蒙街模拟工具网格DAG调度算法性能分析

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This paper presents a solution to analyze the performance of grid scheduling algorithms for tasks with dependencies. Finding the optimal procedures for DAG scheduling in Grid systems is important due to the latest computing necessities: large scale distributed computing and complex applications for different research areas. We propose a solution to evaluate DAG scheduling algorithms using simulation, an approach suitable to evaluate different scheduling algorithms using various task dependencies and considering a wide range of Grid system architectures. Our proposed solution is based on MONARC, a generic simulation framework designed for modeling large scale distributed systems. We present our research results in extending the simulation platform to accommodate various DAG scheduling procedures and, as a case study, we present a critical analysis of four well known DAG scheduling strategies: CCF (Cluster ready Children First), ETF (Earliest Time First), HLFET (Highest Level First with Estimated Times) and Hybrid Remapper. The obtained results show that the proposed solution is a very good instrument for evaluating performance in case of a wide range of DAG scheduling algorithms.
机译:本文提出了一种解决方案,用于分析具有依赖性的任务的网格调度算法的性能。由于最新的计算必需品,查找网格系统中DAG调度的最佳过程很重要:不同研究领域的大规模分布式计算和复杂应用。我们提出了一种使用模拟评估DAG调度算法的解决方案,该方法适于使用各种任务依赖性评估不同调度算法的方法,并考虑各种网格系统架构。我们所提出的解决方案是基于Monarc,一个专为建模大规模分布式系统而设计的通用仿真框架。我们展示了我们的研究导致延长模拟平台,以适应各种DAG调度程序,作为案例研究,我们对四个公知的DAG调度策略提出了批判性分析:CCF(集群准备好儿童首先),ETF(最早的时间) ,HLFET(最高级别首先有估计时间)和混合倒尾。所获得的结果表明,该解决方案是一种非常好的仪器,用于评估性能,在广泛的DAG调度算法。

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