@inproceedings{1dd78fea1f174303992881fbb6837e19,
title = "Improving parallel I/O performance with data layout awareness",
abstract = "Parallel applications can benefit greatly from massive computational capability, but their performance suffers from large latency of I/O accesses. The poor I/O performance has been attributed as a critical cause of the low sustained performance of parallel computing systems. In this study, we propose a data layout-aware optimization strategy to promote a better integration of the parallel I/O middleware and parallel file systems, two major components of the current parallel I/O systems, and to improve the data access performance. We explore the layout-aware optimization in both independent I/O and collective I/O, two primary forms of I/O in parallel applications. We illustrate that the layout-aware I/O optimization could improve the performance of current parallel I/O strategy effectively. The experimental results verify that the proposed strategy could improve parallel I/O performance by nearly 40% on average. The proposed layout-aware parallel I/O has a promising potential in improving the I/O performance of parallel systems.",
keywords = "Collective I/O, Data access optimization, Data layout, I/O performance, Independent I/O, Parallel I/O, Parallel I/O middleware, Parallel file systems",
author = "Yong Chen and Sun, {Xian He} and Rajeev Thakur and Huaiming Song and Hui Jin",
year = "2010",
doi = "10.1109/CLUSTER.2010.35",
language = "English",
isbn = "9780769542201",
series = "Proceedings - IEEE International Conference on Cluster Computing, ICCC",
pages = "302--311",
booktitle = "Proceedings - 2010 IEEE International Conference on Cluster Computing, Cluster 2010",
}