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Parallel and Distributed Processing Symposium, International (2009)
Rome, Italy
May 23, 2009 to May 29, 2009
ISBN: 978-1-4244-3751-1
pp: 1-12
Michael Boyer , Departments of Computer Science, University of Virginia, Charlottesville, 22904, USA
David Tarjan , Departments of Computer Science, University of Virginia, Charlottesville, 22904, USA
Scott T. Acton , Departments of Electrical and Computer Engineering, University of Virginia, Charlottesville, 22904, USA
Kevin Skadron , Departments of Computer Science, University of Virginia, Charlottesville, 22904, USA
ABSTRACT
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 200× 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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CITATION

D. Tarjan, M. Boyer, S. T. Acton and K. Skadron, "Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors," 2009 IEEE International Symposium on Parallel & Distributed Processing (IPDPS), Rome, 2009, pp. 1-12.
doi:10.1109/IPDPS.2009.5160984
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