面向网格计算的机器选择算法研究
Study of a Machine Selection Algorithm for Grid Computing
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摘要: 在以网络为基础的科学与并行计算环境中 ,计算资源具有强分布性、异构性和动态性 当应用程序提交给网格计算环境时 ,需要从全部可用计算资源中选择一个资源子集以支持该应用的执行 复杂的应用问题通常包含多方面的异构性 ,不同性质的应用适合在不同的体系结构运行 基于对网格中可用资源的动态监测与分析结果 ,论文使用模糊聚类方法 ,根据不同的性能指标要求 ,为不同应用选择不同的计算结点集合 将全部可用结点划分为不同的逻辑分组 ,每个分组称为一个逻辑机群 针对应用的不同种类 ,使用λ 截矩阵为每个应用指派一个或多个聚类中心值较大的逻辑机群来协同应用调度 实验表明 ,根据应用类型进行机器选择 ,可以明显改善应用性能 ,通信密集应用选择内部通信性能好的逻辑机群进行调度 ,性能更优、计算密集应用选择计算能力强的逻辑机群进行调度 ,性能明显改善Abstract: For the heterogeneity and distribution of grid computational resources in many aspects, it is important to select a resource subset from all available resources to support an application execution.If assigning the suitable resources to an application, the efficiency of the application will be improved.Usually, a complicated application includes many inherences, and such an application is suitable for execution in machines with different architecture.Based the monitoring results of the resources, a machine selection algorithm with different performance criteria is designed using fuzzy clustering methods.This algorithm clusters all available nodes into several logical groups, and each group is called a logic cluster here.According to the difference of application types, one or several logical clusters suitable for them, with high clustering center value, are selected using the λ-matrix method.The objective of the machine selection based on the application types is to improve the performance of the application scheduler.Test shows that the computation-intensive application is suitable for execution in the logical cluster with high computing capability, and the communication-intensive application is suitable for the logical cluster with high communication performance.
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