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Volume 10, issue 8
Geosci. Model Dev., 10, 2891–2904, 2017
https://doi.org/10.5194/gmd-10-2891-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 2891–2904, 2017
https://doi.org/10.5194/gmd-10-2891-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 01 Aug 2017

Development and technical paper | 01 Aug 2017

GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

Hui Wang et al.

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Chang, J. S., Brost, R. A., Isaksen, I. S. A., Madronich, S., Middleton, P., Stockwell, W. R., and Walcek, C. J.: A three-dimensional Eulerian acid deposition model: Physical concepts and formulation, J. Geophys. Res.-Atmos., 92, 14681–14700, https://doi.org/10.1029/JD092Id12p14681, 1987.
Chen, H. S., Wang, Z. F., Li, J., Tang, X., Ge, B. Z., Wu, X. L., Wild, O., and Carmichael, G. R.: GNAQPMS-Hg v1.0, a global nested atmospheric mercury transport model: model description, evaluation and application to trans-boundary transport of Chinese anthropogenic emissions, Geosci. Model Dev., 8, 2857–2876, https://doi.org/10.5194/gmd-8-2857-2015, 2015.
Chrysos, G.: Intel® Xeon Phi coprocessor (codename Knights Corner), 2012 IEEE Hot Chips 24 Symposium (HCS), 27–29 August 2012, Cupertino, CA, USA, 1–31, 2012.
Feng, F., Wang, Z., Li, J., and Carmichael, G. R.: A nonnegativity preserved efficient algorithm for atmospheric chemical kinetic equations, Appl. Math. Comput., 271, 519–531, https://doi.org/10.1016/j.amc.2015.09.033, 2015.
Ge, B. Z., Wang, Z. F., Xu, X. B., Wu, J. B., Yu, X. L., and Li, J.: Wet deposition of acidifying substances in different regions of China and the rest of East Asia: Modeling with updated NAQPMS, Environ. Pollut., 187, 10–21, https://doi.org/10.1016/j.envpol.2013.12.014, 2014.
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We introduced some methods to port our Global Nested Air Quality Prediction Modeling System (GNAQPMS) model on Intel Knight Landing (KNL). In this paper, we introduced both common and specific methods to accelerate out model better. With the guidance of the resources material on Intel Websites (http://www.intel.com/content/www/us/en/products/processors/xeon-phi.html) and relative books, this paper could be an example for the model developers to take advantage of KNL for their model.
We introduced some methods to port our Global Nested Air Quality Prediction Modeling System...
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