GPU-based asynchronous particle swarm optimization

This paper describes our latest implementation of Particle Swarm Optimization (PSO) with simple ring topology for modern Graphic Processing Units (GPUs). To achieve both the fastest execution time and the best performance, we designed a parallel version of the algorithm, as fine-grained as possible, without introducing explicit synchronization mech- anisms among the particles’ evolution processes. The results we obtained show a significant speed-up with respect to both the sequential version of the algorithm run on an up-to-date CPU and our previously developed parallel implementation within the nVIDIA CUDA architecture.