Title :
GPU-Accelerated Standard and Multi-population Cultural Algorithms
Author :
Jianqiang Dong ; Bo Yuan
Author_Institution :
Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China
Abstract :
In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight benchmark problems, the speedups were only 3-4 times for the standard CA while the multi-population CA can still achieve 30-50 times speedups.
Keywords :
evolutionary computation; graphics processing units; parallel algorithms; parallel architectures; CUDA-enabled GPU; Compute Unified Device Architecture; GPU-accelerated standard; fitness function; graphics processing unit; multipopulation cultural algorithm; parallel cultural algorithms; Benchmark testing; Cultural differences; Graphics processing units; Instruction sets; Sociology; Standards; Statistics; CUDA; GPU; acceleration; clustering; cultural algorithms; multi-population;
Conference_Titel :
Service Sciences (ICSS), 2013 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4673-6258-0
DOI :
10.1109/ICSS.2013.39