Efficient Parallel GPU Design on WRF Five-Layer Thermal Diffusion Scheme

Abstract

Satellite remote-sensing observations and ground-based radar can detect the weather conditions from a distance and are widely used to monitor the weather all around the globe. The assimilated satellite/radar data are passed through the weather models for weather forecasting. The five-layer thermal diffusion scheme is one of the weather models, handling with an energy budget made up of sensible, latent, and radiative heat fluxes. The model feature of no interactions among horizontal grid points makes this scheme very favorable for parallel processing. This study demonstrates implementation of this scheme using graphics processing unit (GPU) massively parallel architecture. By employing one NVIDIA Tesla K40 GPU, our GPU optimization effort on this scheme achieves a speedup of $311 \times$ with respect to its CPU counterpart Fortran code running on one CPU core of Intel Xeon E5-2603, whereas the speedup for one CPU socket (four cores) with respect to one CPU core is only $3.1 \times$ . We can even boost the speedup of this scheme to $398 \times$ with respect to one CPU core when two NVIDIA Tesla K40 GPUs are applied.