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An Analysis of Idle CPU Cycles at University Computer Labs

机译:大学计算机实验室空闲CPU周期分析

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Grid computing has a great potential for grand challenge scientific problems such as Molecular Simulation, High Energy Physics and Genome Informatics. Exploiting under-utilized resources is crucial for a cost-effective, large-scale grid computing platform (i.e., computational grid), but there has been little research work on how to predict what resources will be under-loaded in the near future. In this paper, we analyze idle CPU cycles of PCs at university computer labs and present techniques for predicting idle cycles to be efficiently scheduled for parallel/distributed computing. Our experiments with eight month monitoring data show that the accuracy of our prediction techniques is over 85%. Especially, the ratio of critical failure, which predicts that what is actually busy be idle, was only 3.2% out of total subject PCs during the experimental period.
机译:网格计算具有巨大挑战科学问题的巨大潜力,例如分子模拟,高能物理和基因组信息学等。利用利用的资源对于具有成本效益的大型网格计算平台(即计算网格)至关重要,但是如何预测如何预测在不久的将来将在较近装载的资源的研究工作。在本文中,我们分析了大学计算机实验室的PCS的空闲CPU周期,并提供了用于预测怠速周期的技术,以便有效地调度并行/分布计算。我们的实验有8个月的监测数据显示,我们的预测技术的准确性超过85%。特别是,预测实际忙碌的临界失败的比率在实验期间只有3.2%的基础PC。

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