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Particle Swarm Optimization: A Hardware Implementation

Particle Swarm Optimization (PSO) is a popular population-based optimization algorithm. While PSO has been shown to perform well in a large variety of problems, PSO is typically implemented in software. Population-based optimization algorithms such as PSO are well suited for execution in parallel stages. This allows PSO to be implemented directly in hardware and achieve much faster execution times than possible in software. In this paper, a pipelined architecture for hardware PSO implementation is presented. Benchmark functions solved by software and hardware PSO implementations are compared. The hardware PSO design is implemented on a Xilinx Virtex-II Pro Development Kit for evaluation. By implementing PSO directly on hardware an execution speedup of several orders of magnitude is observed.