Abstract
Uruguay is currently undergoing a gradual process of inclusion of wind energy in its matrix of electric power generation. In this context, a computational tool has been developed to predict the electrical power that will be injected into the grid. The tool is based on the Weather Research and Forecasting (WRF) numerical model, which is the performance bottleneck of the application. For this reason, and in line with several successful efforts of other researchers, this article presents advances in porting the WRF to GPU. In particular, we present the implementation of sintb and bdy_interp1 routines on GPU and the integration of these routines with previous efforts from other authors. The speedup values obtained for the newly ported routines on a Nvidia GeForce GTX 480 GPU are up to \(33.9\times \) when compared with the sequential WRF and \(9.2\times \) when compared with the four-threaded WRF. The integration of the newly ported routines along with previous works produces a reduction of more than a 30 % in the total runtime of the multi-core four-threaded WRF and of more than a 50 % in the single-threaded version.
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Acknowledgments
The authors acknowledge support from Agencia Nacional de Investigación e Innovación (ANII), Administración Nacional de Usinas y Trasmisiones Eléctricas (UTE) and Programa de Desarrollo de las Ciencias Básicas (PEDECIBA), Uruguay.
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Silva, J.P., Hagopian, J., Burdiat, M. et al. Another step to the full GPU implementation of the weather research and forecasting model. J Supercomput 70, 746–755 (2014). https://doi.org/10.1007/s11227-014-1193-y
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DOI: https://doi.org/10.1007/s11227-014-1193-y