DocumentCode
2482537
Title
Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors
Author
Boyer, Michael ; Tarjan, David ; Acton, Scott T. ; Skadro, Kevin
Author_Institution
Depts. of Comput. Sci., Univ. of Virginia, Charlottesville, VA, USA
fYear
2009
fDate
23-29 May 2009
Firstpage
1
Lastpage
12
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 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.
Keywords
biology computing; blood; cellular biophysics; computer graphic equipment; coprocessors; medical image processing; microscopy; object detection; CUDA-capable GPU; leukocyte tracking; manycore coprocessors; programmable manycore CPUs; programmable manycore GPUs; scientific computing; systems biology application; video microscopy; white blood cell detection; white blood cell tracking; Acceleration; Application software; Biology computing; Computer architecture; Concurrent computing; Coprocessors; Iterative algorithms; Programming profession; Systems biology; White blood cells;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
Conference_Location
Rome
ISSN
1530-2075
Print_ISBN
978-1-4244-3751-1
Electronic_ISBN
1530-2075
Type
conf
DOI
10.1109/IPDPS.2009.5160984
Filename
5160984
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