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Grid Scheduling using 2-Phase Prediction (2PP) of CPU Power

机译:CPU功率的2相预测(2PP)网格调度

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Divisible workloads are that kind of workloads that can be partitioned by the scheduler into arbitrary 'chunks'. The problem of scheduling divisible loads has been defined for a long time, however, handful solutions have been proposed. Furthermore, almost all proposed approaches attempt to perform scheduling in a dedicated environment (i.e., for processing local tasks only) such as a LAN, whereas scheduling in non-dedicated environments (i.e., for processing local and external tasks) such as Grids remains an open problem. In Grids, the incessant variation of workstation's power is the chief difficulty in planning how to split and distribute workloads to these workstations. This paper presents a new strategy, called 2-Phase Prediction (2PP) for CPU power. By integrating this strategy and the UMR algorithm, a static scheduling algorithm that is designed for dedicated environments, we develop a new dynamic scheduling algorithm suitable for non-dedicated environment. Our experimental results show that our algorithm is superior to the UMR as the former is able to adapt to the dynamicity of Grid workers.
机译:可分离的工作负载是可以由调度程序分区为任意“块”的那种工作负载。已经定义了调度可分地块的问题很长时间,但是已经提出了少数解决方案。此外,几乎所有提出的方法都尝试在专用环境中执行调度(即,仅用于处理诸如LAN的本地任务),而在非专用环境中调度(即,用于处理本地和外部任务),则诸如网格的诸如网格中的情况仍然存在打开问题。在网格中,工作站的权力的不断变化是规划如何将工作负载分开和分发这些工作站的主要困难。本文提出了一种新的策略,称为CPU电力的2相预测(2PP)。通过集成该策略和UMR算法,我们为专用环境设计了一种静态调度算法,我们开发了一种适用于非专用环境的新动态调度算法。我们的实验结果表明,我们的算法优于UMR,因为前者能够适应网格工人的动态性。

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