Abstract
The aim of this work is to improve load balance of the MPI parallel version of the STEM-II air quality model. Several dynamic data distributions are proposed and evaluated on different systems: homogeneous and dedicated, and heterogeneous and/or non-dedicated. Results prove that dynamic distribution strategies perform better than traditional static distributions. Although all the data distributions presented here have been developed to be used with the STEM–II air quality model, they are also very suitable for use in other parallel applications.
This work has been supported by the Xunta de Galicia (Project PGIPIT04TIC105004PR).
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Mouriño, J.C., Martín, M.J., González, P., Doallo, R. (2006). Dynamic Load-Balancing for the STEM-II Air Quality Model. In: Gavrilova, M., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3980. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751540_74
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DOI: https://doi.org/10.1007/11751540_74
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