16,982 research outputs found
Air pollution modelling using a graphics processing unit with CUDA
The Graphics Processing Unit (GPU) is a powerful tool for parallel computing.
In the past years the performance and capabilities of GPUs have increased, and
the Compute Unified Device Architecture (CUDA) - a parallel computing
architecture - has been developed by NVIDIA to utilize this performance in
general purpose computations. Here we show for the first time a possible
application of GPU for environmental studies serving as a basement for decision
making strategies. A stochastic Lagrangian particle model has been developed on
CUDA to estimate the transport and the transformation of the radionuclides from
a single point source during an accidental release. Our results show that
parallel implementation achieves typical acceleration values in the order of
80-120 times compared to CPU using a single-threaded implementation on a 2.33
GHz desktop computer. Only very small differences have been found between the
results obtained from GPU and CPU simulations, which are comparable with the
effect of stochastic transport phenomena in atmosphere. The relatively high
speedup with no additional costs to maintain this parallel architecture could
result in a wide usage of GPU for diversified environmental applications in the
near future.Comment: 5 figure
The GeoClaw software for depth-averaged flows with adaptive refinement
Many geophysical flow or wave propagation problems can be modeled with
two-dimensional depth-averaged equations, of which the shallow water equations
are the simplest example. We describe the GeoClaw software that has been
designed to solve problems of this nature, consisting of open source Fortran
programs together with Python tools for the user interface and flow
visualization. This software uses high-resolution shock-capturing finite volume
methods on logically rectangular grids, including latitude--longitude grids on
the sphere. Dry states are handled automatically to model inundation. The code
incorporates adaptive mesh refinement to allow the efficient solution of
large-scale geophysical problems. Examples are given illustrating its use for
modeling tsunamis, dam break problems, and storm surge. Documentation and
download information is available at www.clawpack.org/geoclawComment: 18 pages, 11 figures, Animations and source code for some examples at
http://www.clawpack.org/links/awr10 Significantly modified from original
posting to incorporate suggestions of referee
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