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A Survey Paper on Task Scheduling Methods in Cluster Computing Environment for High Performance

机译:高性能集群计算环境中任务调度方法的调查报告

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Parallel computing perform concurrently execution tasks on distributed nodes. Large application split up into tasks and run on number on nodes for high performance computing. Cluster environment composed with heterogeneous devices and software components capable of cost effective and high performance computing on parallel application. In heterogeneous cluster environment proper scheduling of tasks and allocation to nodes is important for high performance computing. Many task scheduling algorithms proposed for achieving high performance computing on heterogeneous computing. We proposed swarm technique methodology for task scheduling on heterogeneous cluster environment, which can perform better results for minimize make span, high performance and resource utilization compared to others.
机译:并行计算在分布式节点上执行并发执行任务。大型应用程序分解为任务,并在节点上大量运行,以实现高性能计算。由异构设备和软件组件组成的集群环境,能够在并行应用程序上进行具有成本效益的高性能计算。在异构集群环境中,正确的任务调度和对节点的分配对于高性能计算很重要。为了在异构计算上实现高性能计算,提出了许多任务调度算法。我们提出了一种用于异构集群环境下的任务调度的群体技术方法,与其他方法相比,该方法可以实现更好的结果,从而最大程度地减少生成跨度,提高性能和资源利用率。

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