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Profiling and Improving I/O Performance of a Large-Scale Climate Scientific Application

Author
Klasky, Scott
Published
July 30, 2013.
Physical Description
1 electronic document
Additional Creators
Yu, Weikuan, Wang, Bin, Liu, Zhuo, Cruz, Carlos A., Clune, Tom, Zhou, Shujia, Xu, Cong, Wang, Yandong, Tian, Yuan, and Wang, Teng
Online Version

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Summary
Exascale computing systems are soon to emerge, which will pose great challenges on the huge gap between computing and I/O performance. Many large-scale scientific applications play an important role in our daily life. The huge amounts of data generated by such applications require highly parallel and efficient I/O management policies. In this paper, we adopt a mission-critical scientific application, GEOS-5, as a case to profile and analyze the communication and I/O issues that are preventing applications from fully utilizing the underlying parallel storage systems. Through in-detail architectural and experimental characterization, we observe that current legacy I/O schemes incur significant network communication overheads and are unable to fully parallelize the data access, thus degrading applications' I/O performance and scalability. To address these inefficiencies, we redesign its I/O framework along with a set of parallel I/O techniques to achieve high scalability and performance. Evaluation results on the NASA discover cluster show that our optimization of GEOS-5 with ADIOS has led to significant performance improvements compared to the original GEOS-5 implementation.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 20140006957.
GSFC-E-DAA-TN9777.
International Conference on Computer Communications and Networks; 30 Jul. - 2 Aug. 2013; Nassau ; Bahamas.
Terms of Use and Reproduction
Copyright, Distribution as joint owner in the copyright.
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