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Journal of Software:2011.22(9):2206-2221

面向并行文件系统的性能评估及相对预测模型
赵铁柱,董守斌,VerdiMARCH,SimonSEE
(华南理工大学 广东省计算机网络重点实验室,广东 广州 510641;五邑大学 计算机学院,广东 江门 529020;Technical and Cloud Computing Center, Oracle Corporation, Singapore;Department of Computer Science, National University of Singapore, Singapore;Technical and Cloud Computing Center, Oracle Corporation, Singapore;Department of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore)
Performance Evaluation and Relative Predictive Model of Parallel File System
ZHAO Tie-Zhu,DONG Shou-Bin,Verdi MARCH,Simon SEE
(Guangdong Key Laboratory of Computer Network, South China University of Technology, Guangzhou 510641, China;School of Computer Science, Wuyi University, Jiangmen 529020, China;Technical and Cloud Computing Center, Oracle Corporation, Singapore;Department of Computer Science, National University of Singapore, Singapore;Technical and Cloud Computing Center, Oracle Corporation, Singapore;Department of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore)
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Received:March 25, 2010    Revised:June 29, 2010
> 中文摘要: 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型(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型(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17%~28%的范围内,易于使用且具有较好的预测准确度.
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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基金项目:国家自然科学基金(10805019); 国家重点基础研究发展计划(973)(2009CB320505); 国家发改委CNGI 项目(CNGI2008-109/122) 国家自然科学基金(10805019); 国家重点基础研究发展计划(973)(2009CB320505); 国家发改委CNGI 项目(CNGI2008-109/122)
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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

ZHAO Tie-Zhu,DONG Shou-Bin,Verdi MARCH,Simon SEE.Performance Evaluation and Relative Predictive Model of Parallel File System.Journal of Software,2011,22(9):2206-2221