Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GCC.2010.34 | GCC |
Keywords | Field | DocType |
lustre,parallel processing,grey systems,grey prediction model,relational analysis model,input-output efficiency,high performance computing system,software performance evaluation,performance factors change,grey theory,basic performance factor,performance model,file organisation,lustre file system,performance evaluation,better prediction precision,deliverable parallel file system,parallel file system,efficient parallel file system,performance change,prediction model,correlation,servers,throughput,predictive models | File system,Supercomputer,Computer science,Grey relational analysis,Server,Real-time computing,Lustre (file system),Test case,Throughput,Lustre (mineralogy),Distributed computing | Conference |
ISBN | Citations | PageRank |
978-0-7695-4313-0 | 3 | 0.50 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tiezhu Zhao | 1 | 17 | 2.35 |
| Jinlong Hu | 2 | 35 | 4.08 |