Simulation of cloud dynamics on graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
A multigrid solver for boundary value problems using programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
The Lattice-Boltzmann Method for Simulating Gaseous Phenomena
IEEE Transactions on Visualization and Computer Graphics
Dispersion Simulation and Visualization For Urban Security
VIS '04 Proceedings of the conference on Visualization '04
UberFlow: a GPU-based particle engine
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
LU-GPU: Efficient Algorithms for Solving Dense Linear Systems on Graphics Hardware
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Integrating particle dispersion models into real-time virtual environments
EGVE'08 Proceedings of the 14th Eurographics conference on Virtual Environments
A parallelization framework for calibration of hydrological models
Environmental Modelling & Software
A high performance GPU implementation of Surface Energy Balance System (SEBS) based on CUDA-C
Environmental Modelling & Software
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Owing to the potential consequences associated with accidental or deliberate releases of chemical or biological agents in urban areas, fast response urban dispersion models must rapidly provide solutions that can be easily analyzed by researchers and emergency responders. In this paper, we describe a novel application of an existing Lagrangian dispersion modeling system to achieve real-time simulation and visualization of an urban plume that a user can interact with in a virtual environment (VE) through the utilization of commodity graphics hardware, utilizing the highly parallel computational capabilities available on graphics processing units (GPU). GPUs have quickly developed from video game technology to open up new avenues for enhancing simulation performance and visualization of engineering and science applications. For computer graphics applications, GPUs provide highly parallel and inexpensive data paths for processing geometry and pixels, but for simulation these parallel paths are exploited for solving general problems. In this paper, a newly developed dispersion model (GPU Plume) is tested against an analytical solution, a CPU implementation of the Lagrangian dispersion model and wind tunnel data for dispersion around a single building. GPU Plume is shown to provide results that are similar in accuracy to the CPU model, but with computation times that are up to two orders magnitude smaller. In addition, challenges associated with the implementation of Lagrangian dispersion models onto the GPU architecture are discussed in this paper.