Utilizing dynamic parallelism in CUDA to accelerate a 3D red-black successive over relaxation wind-field solver
Jan 25, 2021·
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B. Bozorgmehr
P. Willemsen
Jeremy A. Gibbs
R. Stoll
J.-J. Kim
E. Pardyjak
Abstract
QES-Winds is a fast-response wind modeling platform for simulating high-resolution mean wind fields for optimization and prediction. The code uses a variational analysis technique to solve the Poisson equation for Lagrange multipliers to obtain a mean wind field and GPU parallelization to accelerate the numerical solution of the Poisson equation. QES-Winds benefits from CUDA dynamic parallelism (launching the kernel from the GPU) to speed up calculations by a factor of 128 compared to the serial solver for a domain with 145 million cells. The dynamic parallelism enables QES-Winds to calculate mean velocity fields for domains with sizes of 10km2 and horizontal resolutions of 1—3 m in under 1 min. As a result, QES-Winds is a numerical code suitable for computing high-resolution wind fields on large domains in real time, which can be used to model a wide range of real-world problems including wildfires and urban air quality.
Type
Publication
Environmental Modelling and Software, 31, 104958-1–104958-18
Authors
Physical Scientist
I am a Physical Scientist at the NOAA National Severe Storms Laboratory. My research includes computational and theoretical studies of atmospheric boundary-layer flows, turbulence modeling, land-surface modeling, parameterization of boundary-layer and surface-layer interactions, and multi-scale numerical weather prediction. I am currently working on projects to improve atmospheric models in the areas of scale-aware boundary-layer physics, heterogeneous boundary layers, and other storm-scale phenomena.