GPU-based parallel particle swarm optimization

— A novel parallel approach to run standard particle swarm optimization (SPSO) on Graphic Processing Unit (GPU) is presented in this paper. By using the general-purpose computing ability of GPU and based on the software platform of Compute Unified Device Architecture (CUDA) from NVIDIA, SPSO can be executed in parallel on GPU. Experiments are conducted by running SPSO both on GPU and CPU, respectively, to optimize four benchmark test functions. The running time of the SPSO based on GPU (GPU-SPSO) is greatly shortened compared to that of the SPSO on CPU (CPU-SPSO). Running speed of GPU-SPSO can be more than 11 times as fast as that of CPU-SPSO, with the same performance. compared to CPUSPSO, GPU-SPSO shows special speed advantages on large swarm population applications and hign dimensional problems, which can be widely used in real optimizing problems.

• Type: Conference
• Year: 2009
• Where: CEC
• Authors: You Zhou, Ying Tan
• Keywords: Artificial Intelligence, CEC 2009, Compute Unified Device, General-purpose Computing Ability, Particle Swarm Optimization