February 20, 2025
Conference Paper

Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee

Abstract

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 routine Fast Spectral Bin Microphysics (FSBM) 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 an 2.24x overall speedup for the CONUS-12km storm test case.

Published: February 20, 2025

Citation

Wichitrnithed C., W. Yang, Y. He, B. Richardson, K. Sakaguchi, M. Arenaz, and W.I. Gustafson, et al. 2024. Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee. In SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, November 17-22, 2024, Atlanta, GA, 1934-1942. Piscataway, New Jersey:IEEE. PNNL-SA-202641. doi:10.1109/SCW63240.2024.00243

Research topics

Atmospheric Science