Algorithms for bi-objective multiple-choice hardware/software partitioning

This paper proposes three algorithms for multiple-choice hardware-software partitioning with the objectives: minimizing execution time and power consumption, while meeting the area constraint. A heuristic algorithm is proposed to rapidly generate an approximate solution. A tabu search algorithm is customized to refine the heuristic solution. Also, a dynamic programming algorithm is proposed to calculate the exact solution. Simulation results show that the heuristic method produces results that are very close to the exact ones, which can be further refined by tabu search to the solutions with an error of no more than 1.5% for all cases considered in this paper.