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Output performance study on a production petascale filesystem

Publication ,  Conference
Xie, B; Chase, JS; Dillow, D; Klasky, S; Lofstead, J; Oral, S; Podhorszki, N
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2017

This paper reports our observations from a top-tier supercomputer Titan and its Lustre parallel file stores under production load. In summary, we find that supercomputer file systems are highly variable across the machine at fine time scales. This variability has two major implications. First, stragglers lessen the benefit of coupled I/O parallelism (striping). Peak median output bandwidths are obtained with parallel writes to many independent files, with no striping or write-sharing of files across clients (compute nodes). I/O parallelism is most effective when the application—or its I/O middleware system—distributes the I/O load so that each client writes separate files on multiple targets, and each target stores files for multiple clients, in a balanced way. Second, our results suggest that the potential benefit of dynamic adaptation is limited. In particular, it is not fruitful to attempt to identify “good spots” in the machine or in the file system: component performance is driven by transient load conditions, and past performance is not a useful predictor of future performance. For example, we do not observe regular diurnal load patterns.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319676296

Publication Date

January 1, 2017

Volume

10524 LNCS

Start / End Page

187 / 200

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Xie, B., Chase, J. S., Dillow, D., Klasky, S., Lofstead, J., Oral, S., & Podhorszki, N. (2017). Output performance study on a production petascale filesystem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10524 LNCS, pp. 187–200). https://doi.org/10.1007/978-3-319-67630-2_16
Xie, B., J. S. Chase, D. Dillow, S. Klasky, J. Lofstead, S. Oral, and N. Podhorszki. “Output performance study on a production petascale filesystem.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10524 LNCS:187–200, 2017. https://doi.org/10.1007/978-3-319-67630-2_16.
Xie B, Chase JS, Dillow D, Klasky S, Lofstead J, Oral S, et al. Output performance study on a production petascale filesystem. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. p. 187–200.
Xie, B., et al. “Output performance study on a production petascale filesystem.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10524 LNCS, 2017, pp. 187–200. Scopus, doi:10.1007/978-3-319-67630-2_16.
Xie B, Chase JS, Dillow D, Klasky S, Lofstead J, Oral S, Podhorszki N. Output performance study on a production petascale filesystem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. p. 187–200.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319676296

Publication Date

January 1, 2017

Volume

10524 LNCS

Start / End Page

187 / 200

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences