Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee
<|reference_start|>Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee: Currently, the Weather Research and Forecasting model (WRF) utilizes shared memory (OpenMP) and distributed memory (MPI) parallelisms. To take advantage of GPU resources on the Perlmutter supercomputer at NERSC, we port parts of the computationally expensive routines of the Fast Spectral Bin Microphysics (FSBM) microphysical scheme to NVIDIA GPUs using OpenMP device offloading directives. To facilitate this process, we explore a workflow for optimization which uses both runtime profilers and a static code inspection tool Codee to refactor the subroutine. We observe a 2.08x overall speedup for the CONUS-12km thunderstorm test case.<|reference_end|>
@article{chayanon2024optimizing,
    title={Optimizing the Weather Research and Forecasting Model with OpenMP
  Offload and Codee},
    author={Chayanon (Namo) Wichitrnithed, Woo-Sun-Yang, Yun (Helen) He, Brad
  Richardson, Koichi Sakaguchi, Manuel Arenaz, William I. Gustafson Jr., Jacob
  Shpund, Ulises Costi Blanco, Alvaro Goldar Dieste},
    journal={arXiv preprint arXiv:2409.07232},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.07232},
    primaryClass={cs.DC cs.CE}
}