Utilizing dynamic parallelism in CUDA to accelerate a 3D red-black successive over relaxation wind-field solver


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.

Environmental Modelling & Software, 137, 104958
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Dr. Jeremy A. Gibbs
Dr. Jeremy A. Gibbs
Research Meteorologist

My name is Jeremy Gibbs. I am a Research Meteorologist 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.