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

Authors:
Michael Boyer;David Tarjan;Scott T. Acton;Kevin Skadron
Affiliations:
Departments of Computer Science, University of Virginia, Charlottesville, 22904, USA;Departments of Computer Science, University of Virginia, Charlottesville, 22904, USA;Departments of Electrical and Computer Engineering, University of Virginia, Charlottesville, 22904, USA;Departments of Computer Science, University of Virginia, Charlottesville, 22904, USA
Venue:
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Year:
2009

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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脳 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.