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High Performance Computing (HPC) system need to be coupled with efficient parallel file systems, such as Lustre file system, that can deliver commensurate IO throughput to scientific applications. It is important to gain insights into the deliverable parallel file system IO efficiency. In order to gain a good understanding on what and how to impact the performance of parallel file systems. This paper presents a study on performance evaluation of parallel file systems using Lustre file system. We conduct an in-depth survey on the basic performance factors of Lustre. Based on this survey, a series of test cases are designed to validate the performance of Lustre and we adopt relational analysis model and grey prediction model to analyze and predict the performance changes. In our relational analysis, we find that the performance of Lustre has a more closed correlation when performance factors change. Our prediction results indicate that our prediction model can obtain better prediction precision and could be further applied to performance evaluation of other parallel file systems.