Long time-scale simulations of in vivo diffusion using GPU hardware
2009 IEEE International Symposium on Parallel & Distributed Processing, 2009•ieeexplore.ieee.org
To address the problem of performing long time simulations of biochemical pathways under
in vivo cellular conditions, we have developed a lattice-based, reaction-diffusion model that
uses the graphics processing unit (GPU) as a computational co-processor. The method has
been specifically designed from the beginning to take advantage of the GPU's capacity to
perform massively parallel calculations by not only executing a core set of mathematical
calculations, but also running much of the underlying algorithmic logic on the GPU. In this …
in vivo cellular conditions, we have developed a lattice-based, reaction-diffusion model that
uses the graphics processing unit (GPU) as a computational co-processor. The method has
been specifically designed from the beginning to take advantage of the GPU's capacity to
perform massively parallel calculations by not only executing a core set of mathematical
calculations, but also running much of the underlying algorithmic logic on the GPU. In this …
To address the problem of performing long time simulations of biochemical pathways under in vivo cellular conditions, we have developed a lattice-based, reaction-diffusion model that uses the graphics processing unit (GPU) as a computational co-processor. The method has been specifically designed from the beginning to take advantage of the GPU's capacity to perform massively parallel calculations by not only executing a core set of mathematical calculations, but also running much of the underlying algorithmic logic on the GPU. In this study we present our three-dimensional model for in vivo diffusion that exploits the calculation capabilities of the GPU. The implementation of the diffusion operator on the GPU is subject to architectural constraints, and we discuss its structure and the trade-offs made to accommodate the GPU hardware.
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