AN OPTIMIZATION OF A GPU-BASED PARALLEL WIND FIELD MODULE

Atmospheric radionuclide dispersion systems (ARDS) are important tools to predict the impact of radioactive releases from Nuclear Power Plants and guide people evacuation from affected areas. Four modules comprise ARDS: Source Term, Wind Field, Plume Dispersion and Doses Calculations. The slowest is the Wind Field Module that was previously parallelized using the CUDA C language. The statement purpose of this work is to show the speedup gain with the optimization of the already parallel code of the GPU-based Wind Field module, based in WEST model (Extrapolated from Stability and Terrain). Due to the parallelization done in the wind field module, it was observed that some CUDA processors became idle, thus contributing to a reduction in speedup. It was proposed in this work a way of allocating these idle CUDA processors in order to increase the speedup. An acceleration of about 4 times can be seen in the comparative case study between the regular CUDA code and the optimized CUDA code. These results are quite motivating and point out that even after a parallelization of code, a parallel code optimization should be taken into account