Regional Climate Model for the Lower Volga: Parallelization Efficiency Estimation

Alexander V. Titov, Alexander V. Khoperskov

Abstract


We have deployed the regional climate model (RCM) RegCM 4.5 for the Lower Volga and adjacent territories with a horizontal spatial resolution of 20 km. The problems of choosing the computational domain in the RCM RegCM version 4.5 are considered. We demonstrate the influence of this factor on the forecast of rainfall distribution in the numerical simulations. The study of rainfall and snowfall is a more demanding test in comparison with temperature or pressure distributions. We investigate dependencies of calculation time, parallel speedup and parallelization efficiency on the number of processes for different multi-core CPUs. Our analysis of the efficiency of parallel implementation of RegCM for various multi-core and multi-processor systems show a strong dependence of the simulation speed on the CPU type. The best effect is achieved when the number of CPU threads and the number of parallel processes are equal. The parallel code speedup is in the range of 1.8 – 11 for different CPUs.


Full Text:

PDF

References


Hui, P., Tang, J., Wang, S., Wu, J., Kang, Y.: Future climate projection under IPCC A1B scenario in the source region of Yellow River with complex topography using RegCM3. Journal of Geophysical Research: Atmospheres 119(19), 11,205–11,222 (2014), DOI: 10.1002/2014JD021992

Kalugin, A.S., Motovilov, Y.G.: Runoff Formation Model for the Amur River Basin. Water Resources 45(2), 121–132 (2018), DOI: 10.7868/S0321059618020013

Khrapov, S., Khoperskov, A.: Smoothed-Particle Hydrodynamics Models: Implementaon Features on GPUs. Communications in Computer and Information Science 793, 266–277 (2017), DOI: 10.1007/978-3-319-71255-0 21

Kuhn, M., Kunkel, J., Ludwig, T.: Data Compression for Climate Data. Supercomputing Frontiers and Innovations 3(1), 75–94 (2016), DOI: 10.14529/jsfi160105

Politi, N., Nastos, P., Sfetsos, A., Vlachogiannis, D., Dalezios, N.: Evaluation of the AWRWRF model configuration at high resolution over the domain of Greece. Atmospheric Research 208, 229–245 (2018), DOI: 10.1016/j.atmosres.2017.10.019

Raghavan, S.V., Liu, J., Nguyen, N.S., Vu, M.T., Liong, S.Y.: Assessment of CMIP5 historical simulations of rainfall over Southeast Asia. Theoretical and Applied Climatology 132(3), 989–1002 (2018), DOI: 10.1007/s00704-017-2111-z

Wang, Y., Leung, L.R., McGregor, J.L., Lee, D.K., Wang, W.C., Ding, Y., Kimura, F.: Regional Climate Modeling: Progress, Challenges, and Prospects. Journal of the Meteorological Society of Japan. Ser. II 82(6), 1599–1628 (2004), DOI: 10.2151/jmsj.82.1599

Wang, Y., Jiang, J., Zhang, J., He, J., Zhang, H., Chi, X., Yue, T.: An efficient parallel algorithm for the coupling of global climate models and regional climate models on a large-scale multi-core cluster. Journal of Supercomputing 74(8), 3999–4018 (2018), DOI: 10.1007/s11227-018-2406-6




Publishing Center of South Ural State University (454080, Lenin prospekt, 76, Chelyabinsk, Russia)