文献类型：会议论文

英文题名：Transferring performance prediction models across different hardware platforms

作者：Valov, Pavel[1]; Petkovich, Jean-Christophe[1]; Guo, Jianmei[2]; Fischmeister, Sebastian[1]; Czarnecki, Krzysztof[1]

机构：[1] University of Waterloo, 200 University Avenue, West Waterloo, ON, Canada; [2] East China University of Science and Technology, 130 Meilong Road, Shanghai, China

会议论文集：ICPE 2017 - Proceedings of the 2017 ACM/SPEC International Conference on Performance Engineering

会议日期：April 22, 2017 - April 26, 2017

会议地点：L'Aquila, Italy

语种：英文

外文关键词：Computer software

摘要：Many software systems provide configuration options relevant to users, which are often called features. Features inuence functional properties of software systems as well as non-functional ones, such as performance and memory consumption. Researchers have successfully demonstrated the correlation between feature selection and performance. However, the generality of these performance models across different hardware platforms has not yet been evaluated. We propose a technique for enhancing generality of performance models across different hardware environments using linear transformation. Empirical studies on three real-world software systems show that our approach is computationally efficient and can achieve high accuracy (less than 10% mean relative error) when predicting system performance across 23 different hardware platforms. Moreover, we investigate why the approach works by comparing performance distributions of systems and structure of performance models across different platforms. ? 2017 ACM.