Evaluation of a Performance Model of Lustre File System

Abstract

As a large-scale global parallel file system, Lustre file system plays a key role in High Performance Computing (HPC) system, and the potential performance of such systems can be difficult to predict because the potential impact to application performance is not clearly understood. It is important to gain insights into the deliverable Lustre file system IO efficiency. In order to gain a good understanding on what and how to impact the performance of Lustre file system. This paper presents a study on performance evaluation of Lustre file systems and we propose a novel relative performance model to predict overhead under different performance factors. In our previous experiments, we discover that different performance factors have a closed correlation. In order to mining the correlations, we introduce relative performance model to predict performance differences between a pair of Lustre file system equipped with different performance factors. On average, relative model can predict bandwidth within 17%-28%. The results show our relative prediction model can obtain better prediction accuracy.