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

This paper proposes three algorithms for multiple-choice hardware-software partitioning with the objectives of minimizing execution time and power consumption, while meeting area constraint. Firstly, a heuristic algorithm is proposed to rapidly generate an approximate solution. In the second algorithm we refined the approximate solution using a customized tabu search algorithm. Finally, a dynamic programming algorithm is proposed to calculate the exact solution. Simulation results show that the approximate solution is very close to the exact solution. This can be further refined by tabu search to achieve a solution with less than 1.5% error for all cases considered in this paper.