Efficient Implementation of Particle Swarm Optimization Algorithm

Abstract: Dataflow representations have been developing since the 1980’s. They have proven to be useful in identifying bottlenecks in DSP algorithms, improving the efficiency of the computations, and in designing appropriate hardware for implementing the algorithms. This paper extends and demonstrates the use of dataflow-based methodology, called as Reactive Control-integrated Dataflow based Aggressive Forwarding Check (RCDF-AFC), to implement a Particle Swarm Optimization (PSO) algorithm in hardware-software co-design. PSO has been extensively used in the real world but its application has been limited to relatively slow processes because it is computationally intensive. It is shown that the time required for the PSO computations using extensive iteration for solving the optimization problem can be reduced by means of dataflow based analysis and implementation improvements based on these analyses.

Keywords: Particle swarm optimization (PSO), Model Predictive Control (MPC).

R. Gu is with Microsoft, One Microsoft Way Redmond, WA, 98052, ruiruigu@microsoft.com
Z. Shi is with University of Missouri – Kansas City, zhefushi@mail.umkc.edu

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Cite: Ruirui Gu, Zhefu Shi, "Efficient Implementation of Particle Swarm Optimization Algorithm," Progress in Intelligent Computing and Applications , vol. 4, no. 1, pp. 1-9, March 2015.