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I/O in WRF: A Case Study in Modern Parallel I/O Techniques

Published: 11 November 2023 Publication History

Abstract

Large-scale parallel applications can face significant I/O performance bottlenecks, making efficient I/O crucial. This work presents a comparative study of several parallel I/O implementations in the Weather Research and Forecasting model, including PnetCDF blocking and non-blocking I/O options, netCDF4, HDF5 Log VOL, and ADIOS. For I/O methods creating files in a canonical data layout, PnetCDF's non-blocking option offers up to 2x improvement over its blocking option and up to 4.5x over HDF5 via netCDF4, demonstrating the effectiveness of the write request aggregation technique. The HDF5 Log VOL outperforms ADIOS with a 4x improvement in write performance when creating files in the log layout, although both require non-negligible time to convert the file back to canonical order for post-run analysis. From these results we extract some observations that can guide I/O strategies for modern parallel codes.

Supplemental Material

MP4 File - SC23 paper presentation recording for "I/O in WRF: A Case Study in Modern Parallel I/O Techniques"
SC23 paper presentation recording for "I/O in WRF: A Case Study in Modern Parallel I/O Techniques", by Zanhua Huang, Kaiyuan Hou, Ankit Agrawal, Alok Choudhary, Robert Ross and Wei-Keng Liao

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    cover image ACM Conferences
    SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
    November 2023
    1428 pages
    ISBN:9798400701092
    DOI:10.1145/3581784
    Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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    Published: 11 November 2023

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    1. parallel I/O
    2. I/O performance tuning
    3. benchmarking
    4. WRF

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