Hardware Software Partitioning Problem in Embedded System Design Using Particle Swarm Optimization Algorithm

Hardware/software partitioning is a crucial problem in embedded system design. In this paper, we provide an alternative approach to solve this problem using particle swarm optimization (PSO) algorithm. Performance analysis of the proposed scheme with integer linear programming, genetic algorithm and ant colony optimization technique has been compared using standard benchmark datasets, and the computer simulations reveal that the proposed approach outperforms all the meta-heuristic based existing techniques with respect to cumulative runtimes for several runs of the same program. The integer linear programming has been found to yield the optimal solutions, and the proposed swarm scheme yields sub-optimal solution, sufficiently close to the reported results obtained for integer programming.

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