论文信息 - SOPC-Based Architecture for Discrete Particle Swarm Optimization

SOPC-Based Architecture for Discrete Particle Swarm Optimization

The complexity of modern chips is rising and fundamental changes in system design are necessary. System- on-a-Programmable-Chip (SOPC) concept is bringing a major revolution in the design of integrated circuits due to the flexibility it provides and the complexity it caters to. Particle Swarm Optimization (PSO) is a powerful function optimizer that is successfully used to solve problems in numerous fields. The main downside of PSO is that it has significant computation time because of sequential execution of software implementations. In this paper, an SOPC-based PSO framework is proposed. By implementing a hardware/software co-design of PSO, most of the computations can simultaneously be performed using hardware to reduce the computation time, while keeping the flexibility of software. The results indicate a speed-up of up to 100 times in the elapsed computation time.

Amin Farmahini Farahani | Sied Mehdi Fakhraie | Saeed Safari

[1] Robert J. Marks,et al. FPGA implementation of particle swarm optimization for inversion of large neural networks , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[2] Russell C. Eberhart,et al. Recent advances in particle swarm , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[3] Gabriella Kókai,et al. Using Hardware-Based Particle Swarm Method for Dynamic Optimization of Adaptive Array Antennas , 2006, First NASA/ESA Conference on Adaptive Hardware and Systems (AHS'06).

[4] K. Dejong,et al. An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[5] Zdenek Konfrst,et al. Parallel Genetic Algorithms: Advances, Computing Trends, Applications and Perspectives , 2004, IPDPS.

[6] R. Eberhart,et al. Particle Swarm Optimization-Neural Networks, 1995. Proceedings., IEEE International Conference on , 2004 .

[7] Zhenhuan Zhu,et al. A Novel Genetic Algorithm Designed for Hardware Implementation , 2007 .

[8] Peter Martin,et al. An Analysis Of Random Number Generators For A Hardware Implementation Of Genetic Programming Using FPGAs And Handel-C , 2002, GECCO.

[9] Russell C. Eberhart,et al. A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.