Particle swarm optimizer tracking based on DSP parallel system

For the problem of a large amount and slow speed in the serial Particle Swarm Optimization (PSO) algorithm, a parallel PSO tracking algorithm based on Digital Signal Processing (DSP) parallel system is proposed. In the development of the four DSP parallel systems, a parallel PSO tracking algorithm is designed using the message passing model and the Master-Slave mode of a single species. The initial setting is realized by DSP-A, while DSP-B, DSP-C and DSP-D are used to calculate the fitness of each particle in parallel. Finally, the fitness of each particle and the pros and cons of individual extreme are compared by DSP-A, and then a better individual extreme and an optimal solution of the entire population are chosen to update the position and velocity of each particle. Comparing with the serial PSO algorithm, the speedup ratio and efficiency of the simulation algorithm based on the actual sequence of image are 2.525 and 63.13%, respectively. The method supplies a new option to implement a large-scale global optimization target tracking project.