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
Link To Document :
بازگشت