 |
    |
Parallelization Strategies for Hybrid Metaheuristics Using a Single GPU and Multi-core Resources
Thé Van Luong1, Eric Taillard1, Nouredine Melab2, and El-Ghazali Talbi2
1HEIG-VD, Yverdon-les-Bains, Switzerland
Eric.Taillard@heig-vd.ch
2INRIA Lille Nord Europe / LIFL, Villeneuve d’Ascq, France
Nouredine.Melab@lifl.fr
talbi@lifl.fr
Abstract. Hybrid metaheuristics are powerful methods for solving complex problems in science and industry. Nevertheless, the resolution time remains prohibitive when dealing with large problem instances. As a result, the use of GPU computing has been recognized as a major way to speed up the search process. However, most GPU-accelerated algorithms of the literature do not take benefits of all the available CPU cores. In this paper, we introduce a new guideline for the design and implementation of effective hybrid metaheuristics using heterogeneous resources.
LNCS 7492, p. 368 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012