Robert Patro, John P. Dickerson, Sujal Bista, Satyandra K. Gupta, Amitabh Varshney
In this paper, we introduce a graphic processing unit (GPU)-based framework for simulating particle trajectories under both static and dynamic force fields. By exploiting the highly parallel nature of the problem and making efficient use of the available hardware, our simulator exhibits a significant speedup over its CPU-based analog. We apply our framework to a specific experimental simulation: the computation of trapping probabilities associated with micron-sized silica beads in optical trapping workbenches. When evaluating large numbers of trajectories (4096), we see approximately a 356 times speedup of the GPU-based simulator over its CPU-based counterpart.
DOI
In this paper, we introduce a graphic processing unit (GPU)-based framework for simulating particle trajectories under both static and dynamic force fields. By exploiting the highly parallel nature of the problem and making efficient use of the available hardware, our simulator exhibits a significant speedup over its CPU-based analog. We apply our framework to a specific experimental simulation: the computation of trapping probabilities associated with micron-sized silica beads in optical trapping workbenches. When evaluating large numbers of trajectories (4096), we see approximately a 356 times speedup of the GPU-based simulator over its CPU-based counterpart.
DOI
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