Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors
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}
}
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.
November 26, 2010 by hgpu
