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

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.