Chaotic multi-group optimization algorithm based on heterogeneous computing

Runjie Liu; Genhao Cai; Le Chen; Siqi Wang

doi:10.1117/12.3011967

7 December 2023 Chaotic multi-group optimization algorithm based on heterogeneous computing

Runjie Liu, Genhao Cai, Le Chen, Siqi Wang

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129411P (2023) https://doi.org/10.1117/12.3011967
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Traditional particle swarm optimization has attracted attention in various fields because of its relatively simple form and flexible parameter setting, but it also has the disadvantages of slow convergence speed and easy to fall into local optimization in the face of large-scale multivariate data. To solve this kind of problem, a chaotic multi-group optimization algorithm (CM-PSO) based on Graphics Processing Unit (GPU) is proposed. In the algorithm initialization stage, chaotic mapping is introduced to enhance population diversity, and then the population is divided into multiple small subgroups according to the idea of island model, and the Feng's topology is adopted within each subgroup to improve the search efficiency and reduce the computational complexity. Finally, the CUDA stream (streams) technology is used to realize grid-level parallelism, further improve the degree of algorithm parallelism, and improve the algorithm performance while ensuring the accuracy of the algorithm.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Runjie Liu, Genhao Cai, Le Chen, and Siqi Wang "Chaotic multi-group optimization algorithm based on heterogeneous computing", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129411P (7 December 2023); https://doi.org/10.1117/12.3011967

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KEYWORDS

Particles

Particle swarm optimization

Mathematical optimization

Chaos

Image processing

Algorithm development

Evolutionary algorithms

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