Presentation
Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee
DescriptionCurrently, 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.
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.
Author/Presenters
