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Application performance prediction method based on cross-core performance interference on multi-core processor

机译:基于跨核性能干扰的多核处理器应用性能预测方法

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Due to the contention for shared resource, applications deployed on different cores would suffer from the performance interference. Therefore, how to predict applications performance reasonably has become the hotspot in current studies. A challenges of the existing application performance prediction methods are hard to determine the pressure indicators and assess the pressure of the multi-interference application forcing, this paper proposes an application performance prediction method which is based on the cross core performance interference on multi-core processors. In particular, we firstly analyze the relationship between the cross-core shared resource usage and the performance degradation of applications. Then, we- select the appropriate indicators to represent the pressure on shared resources using the correlation analysis, and establish the correlation model between the degree of the performance degradation and the pressure level by using the stepwise regression analysis method. Meanwhile, we consider the mutual of the interference and employ a K-means clustering algorithm to decrease the prediction cost. Experimental results show that the pressure indicators could measure the competition to the resource and the performance model could predict the performance degradation accurately. (C) 2016 Elsevier B.V. All rights reserved.
机译:由于共享资源的争夺,部署在不同核心上的应用程序将遭受性能干扰。因此,如何合理地预测应用程序性能已成为当前研究的热点。现有应用性能预测方法面临的挑战是难以确定压力指标和评估多干扰应用强迫的压力,本文提出了一种基于跨核性能干扰的应用性能预测方法。 。特别是,我们首先分析跨核心共享资源的使用与应用程序性能下降之间的关系。然后,我们通过相关分析选择合适的指标来表示共享资源的压力,并通过逐步回归分析方法建立性能下降程度与压力水平之间的相关模型。同时,考虑了干扰的相互影响,采用K-means聚类算法降低了预测成本。实验结果表明,压力指标可以衡量对资源的竞争程度,而性能模型可以准确预测性能下降。 (C)2016 Elsevier B.V.保留所有权利。

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