Sen, K and Vadhiyar, S and Vinayachandran, PN (2023) Strategies for Fast I/O Throughput in Large-Scale Climate Modeling Applications. In: 30th Annual IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2023, Proceedings - 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics, HiPC 2023, Goa, pp. 203-212.
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Abstract
Large-scale HPC applications are highly data-intensive with significant times spent in I/O operations. Many large-scale scientific applications do not adequately optimize the I/O operations, leading to overall poor performance. In this work, we have developed two main strategies for providing fast I/O throughput for an important climate modeling application, namely, Regional Ocean Modeling System (ROMS) that uses NetCDF for I/O operations. The strategies include load balancing the I/O operations and selective writing of data. We have also implemented file striping to improve I/O performance. Our experiments with up to 1440 processor cores and 5 days of simulations showed that our load balancing strategy resulted in about 27 decrease in execution times over the default executions, our selective writing strategy resulted in a further decrease of about 30 and the optimized file striping resulted in a further decrease of about 12 in execution times. All the strategies combined together improved the overall performance of the application by about 70. © 2023 IEEE.
Item Type: | Conference Paper |
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Publication: | Proceedings - 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics, HiPC 2023 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc. |
Keywords: | Collective I/O; Data intensive; Large-scales; Luster striping; Model application; Netcdf; Parallel I/O; Performance; Regional ocean modeling system; Regional ocean modeling system climate model, Climate models |
Department/Centre: | Division of Interdisciplinary Sciences > Computational and Data Sciences Division of Mechanical Sciences > Centre for Atmospheric & Oceanic Sciences |
Date Deposited: | 02 Sep 2024 10:11 |
Last Modified: | 02 Sep 2024 10:11 |
URI: | http://eprints.iisc.ac.in/id/eprint/84953 |
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