Title :
A Parallel Immune Algorithm Based on Fine-Grained Model with GPU-Acceleration
Author :
Li, Jianming ; Zhang, Lihua ; Liu, Linlin
Author_Institution :
Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol., Dalian, China
Abstract :
Fine-grained parallel immune algorithm (FGIA), though a popular and robust strategy for solving complicated optimization problems, is sometimes inconvenient to use as its population size is restricted by heavy data communication and the parallel computers are relatively difficult to use, manage, maintain and may not be accessible to most researchers. In this paper, we propose a FGIA method based on GPU-acceleration, which maps parallel IA algorithm to GPU through the CUDA. We implement the IA on the base of the framework of genetic algorithm (GA), the analytical results demonstrate that the proposed method increases the population size, speeds up its execution and provides ordinary users with a feasible FGIA solution.
Keywords :
artificial immune systems; computer graphics; coprocessors; genetic algorithms; parallel algorithms; CUDA; GPU acceleration; data communication; fine-grained parallel immune algorithm; genetic algorithm; graphical processing unit; parallel computers; Cities and towns; Computer networks; Concurrent computing; Data communication; Distributed computing; Genetic algorithms; Immune system; Optimization methods; Parallel machines; Robustness;
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
DOI :
10.1109/ICICIC.2009.44