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Dynamic Load Balancing Using Periodically Load Collection with Past Experience Policy on Linux Cluster System

机译:在Linux群集系统上使用定期负载收集和过去的经验策略进行动态负载平衡

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Fast execution of the applications achieved through parallel execution of the processes. This is very easily achieved by high performance cluster (HPC) through concurrent processing with the help of its compute nodes. The HPC cluster provides super computing power using execution of dynamic load balancing algorithm on compute nodes of the clusters. The main objective of dynamic load balancing algorithm is to distribute even workload among the compute nodes for increasing overall efficiency of the clustered system. The logic of dynamic load balancing algorithm needs parallel programming. The parallel programming on the HPC cluster can achieve through massage passing interface in C programming. The MPI library plays very important role to build new load balancing algorithm. The workload on a HPC cluster system can be highly variable, increasing the difficulty of balancing the load across its compute nodes. This paper proposes new idea of existing dynamic load balancing algorithm, by mixing centralized and decentralized approach which is implemented on Rock cluster and maximum time it gives the better performance. This paper also gives comparison between previous dynamic load balancing algorithm and new dynamic load balancing algorithm.
机译:通过并行执行流程可以快速执行应用程序。高性能群集(HPC)在其计算节点的帮助下通过并发处理非常容易实现这一点。 HPC群集通过在群集的计算节点上执行动态负载平衡算法来提供超级计算能力。动态负载平衡算法的主要目标是在计算节点之间平均分配工作负载,以提高集群系统的整体效率。动态负载平衡算法的逻辑需要并行编程。 HPC集群上的并行编程可以通过C编程中的消息传递接口来实现。 MPI库在构建新的负载平衡算法中扮演着非常重要的角色。 HPC群集系统上的工作负载可能变化很大,从而增加了在其计算节点之间平衡负载的难度。本文提出了一种新的思想,即现有的动态负载平衡算法,将在摇滚集群上实现的集中式和分散式方法相结合,并在最长的时间内给出了更好的性能。本文还比较了以前的动态负载平衡算法和新的动态负载平衡算法。

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