Performance Evaluation and Relative Predictive Model of Parallel File System
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    Abstract:

    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.

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赵铁柱,董守斌,Verdi MARCH, Simon SEE.面向并行文件系统的性能评估及相对预测模型.软件学报,2011,22(9):2206-2221

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  • Received:March 25,2010
  • Revised:June 29,2010
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