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The availability of easily programmable manycore CPUs and GPUs has motivated investigations into how to best exploit their tremendous computational power for scientific computing. Here the authors demonstrate how a systems biology application - detection and tracking of white blood cells in video microscopy - can be accelerated by 200x using a CUDA-capable GPU. Because the algorithms and implementation challenges are common to a wide range of applications, they discuss general techniques that allow programmers to make efficient use of a manycore GPU.
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