Predicting Performance of Non-contiguous I/O with Machine Learning-Reference-Cited by-同舟云学术

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Predicting Performance of Non-contiguous I/O with Machine Learning

Published:2015 Issue: Volume: Page:257-273
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Kunkel Julian,Zimmer Michaela,Betke Eugen

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-20119-1_19

Reference18 articles.

1. Thakur, R., Gropp, W., Lusk, E.: Data sieving and collective I/O in ROMIO. In: FRONTIERS 1999: Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation, p. 182. IEEE Computer Society, Washington, DC (1999)

2. Ching, A., Choudhary, A., Coloma, K., Liao, W.K., Ross, R., Gropp, W.: Noncontiguous I/O accesses through MPI-IO. In: Proceedings of the 3rd International Symposium on Cluster Computing and the Grid, CCGRID, p. 104. IEEE Computer Society, Washington, DC (2003)

3. Singh, D.E., Isaila, F., Calderon, A., Garcia, F., Carretero, J.: Multiple-phase collective I/O technique for improving data access locality. In: Proceedings of the 15th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP, pp. 534–542. IEEE Computer Society, Washington, DC (2007)

4. Singh, D.E., Isaila, F., Pichel, J.C., Carretero, J.: A collective I/O implementation based on inspector-executor paradigm. J. Supercomputing 47(1), 53–75 (2009)

5. Lecture Notes in Computer Science;X Zhang,2014

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