面向并行文件系统的性能评估及相对预测模型

Performance Evaluation and Relative Predictive Model of Parallel File System

基于Lustre文件系统，对并行文件系统的性能评估和性能建模进行了研究．通过对性能因子的调研，进行了一系列性能评估实验，并提出性能相关性模~（PRModel）．在实验评估和PRModel分析中发现，在不同的性能因子之间存在着紧密的性能相关性，为了挖掘并利用这种相关性信息，提出了一种相对性能预测模（RPPModel）来预测不同性能因子条件下的性能．为了验证RPPModel的有效性，设计了大量实验用例．结果表明，预测结果的平均相对误差能够控制在170／o---28％的范围内，易于使用且具有较好的预测准确度．

In this paper, the performance evaluation and modeling of parallel file system based on Lustre file system is studied. After performing a survey on performance factors, a series of performance evaluations via experimental approaches and propose a performance relational model （PRModel）. In the experimental and PRModel analysis, it is found that different performance factors have closed performance correlations. In order to mime the relational information, a novel relative performance predictive model （RPPModel） is proposed. This model can be used to predict the overhead over different performance factors. The model is validated through a series of experiments over a variety of performance factors. The experimental results show that the average relative errors results can be controlled within 17%-28%. This model is easy to use and can obtain better prediction accuracy.