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Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors

M. Boyer, D. Tarjan, S. T. Acton, K. Skadron
Departments of Computer Science, University of Virginia, Charlottesville, VA 22904
Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on In IEEE International Symposium on Parallel & Distributed Processing (IPDPS’09) (May 2009), pp. 1-12

@article{boyer2009accelerating,

   title={Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors},

   author={Boyer, M. and Tarjan, D. and Acton, S.T. and Skadron, K.},

   year={2009},

   publisher={IEEE}

}

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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 we demonstrate how a systems biology application – detection and tracking of white blood cells in video microscopy – can be accelerated by 200times using a CUDA-capable GPU. Because the algorithms and implementation challenges are common to a wide range of applications, we discuss general techniques that allow programmers to make efficient use of a manycore GPU.
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