TY - JOUR
KW - Genetic Algorithms
KW - GPGPU
KW - Parallel Processing
AU - Álvaro Arranz
AU - Manuel Alvar
AB - During the last decade, the general-purpose computing on graphics processing units Graphics  (GPGPU) has turned out to be a useful tool for speeding up many scientific calculations. Computer vision is known to be one of the fields with more penetration of these new techniques.   This paper explores the advantages of using GPGPU implementation to speedup a genetic algorithm used for stereo refinement.  The main contribution of this paper is analyzing which genetic operators take advantage of a parallel approach and the description of an efficient state- of-the-art implementation for each one. As a result, speed-ups close to x80 can be achieved, demonstrating to be the only way of achieving close to real-time performance.
IS - Special Issue on Digital Economy
M1 - 2
N2 - During the last decade, the general-purpose computing on graphics processing units Graphics  (GPGPU) has turned out to be a useful tool for speeding up many scientific calculations. Computer vision is known to be one of the fields with more penetration of these new techniques.   This paper explores the advantages of using GPGPU implementation to speedup a genetic algorithm used for stereo refinement.  The main contribution of this paper is analyzing which genetic operators take advantage of a parallel approach and the description of an efficient state- of-the-art implementation for each one. As a result, speed-ups close to x80 can be achieved, demonstrating to be the only way of achieving close to real-time performance.
PY - 2015
SP - 69
EP - 76
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - GPGPU Implementation of a Genetic Algorithm for Stereo Refinement
UR - http://www.ijimai.org/JOURNAL/sites/default/files/files/2015/02/ijimai20153_2_9.pdf
VL - 3
SN - 1989-1660
ER -