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Development of a new methodology for improving urban fast response lagrangian dispersion simulation via parallelism on the graphics processing unit

INTRODUCTION Recent trends in computing have shifted toward multi-core processors and programmable graphics processors with highly parallel data paths for processing geometry and pixels. Multi-core machines are now readily available with 2 cores, but machines with 4, 8, and even 16 cores are projected for the near future. Data parallelism in modern graphics cards is also increasing with raw performance of graphics processing units (GPUs) surpassing performance of CPUs. While initially specialized for processing computer graphics, GPUs can be programmed for general-purpose computations using high level programming languages similar to C. As a result, GPUs have become useful computational tools providing highly parallel data paths to accelerate a wide range of scientific and simulation applications.