DOI: 10.14704/nq.2018.16.5.1304

A Discrete Multi-Objective Optimization Method for Hardware/Software Partitioning Problem Based on Cuckoo Search and Elite Strategy

Wei Xiong, Bing Guo, Yan Shen, Wenli Zhang


This paper attempts to provide a desirable solution to hardware/software partitioning of the embedded system. For this purpose, the author developed a discrete multi-objective optimization method based on the cuckoo search (CS) algorithm (MODCS) and the elite strategy of stratification and congestion degree comparison. Then, the MODCS was compared with two other typical simulation algorithms. The results show that the MODCS is superior to typical optimization algorithms in terms of many indices, including diversity, stability and generational distance (GD) of optimal solution. The superiority is positively correlated with the number of modules. The findings shed new light on the bionic optimization of hardware/software partitioning.


Multi-objective Simulation, Hardware/Software Partitioning, Cuckoo Search, Elite Strategy, Generational Distance (GD), Pareto Diversity

Full Text:



Savage, M. J. W., Salcic, Z., Coghill, G., & Covic, G. (2004). Extended genetic algorithm for codesign optimization of DSP systems in FPGAs. IEEE International Conference on Field-Programmable Technology, 2004. Proceedings (pp.291-294).

Barthelemy P, Bertolotti J, Wiersma DS. A Lévy flight for light. Nature 2008; 453(7194):495.

Coello CAC, Lechuga MS. MOPSO: a proposal for multiple objective particle swarm optimization, Evolutionary Computation, 2002. CEC '02, Proceedings of the 2002 Congress on, IEEE 2002; 1051-56.

Deb K, Pratap A, Agarwal S, Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation 2002; 6(2): 182-97.

Deb K. Multi-objective optimization using evolutionary algorithms, New York: John Wiley & Sons, 2001.

Ernst R, Henkel J, Benner T. Hardware-Software Cosynthesis for Microcontrollers. Design & Test of Computers IEEE, 1993; 10(4): 64-75.

Garey MR, Johnson DS. Computers and intractability: A guide to the theory of NP-completeness, W H Freeman Company, 1979.

Guo B, Wang D, Shen Y, Liu Z. Hardware–software partitioning of real-time operating systems using Hopfield neural networks. Neurocomputing 2006; 69(16-18): 2379-84.

Konak A, Coit DW, Smith AE. Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety 2006; 91(9): 992-1007.

Ma T, Wang X, Li Z. Neural Network Optimization for Hardware-Software Partitioning, International Conference on Innovative Computing, Information and Control. IEEE Computer Society 2006; 423-26.

Pan Z. Hardware-software partitioning for the design of system on chip by neural network optimization method, International Symposium on Precision Engineering Measurements and Instrumentation, International Society for Optics and Photonics, 2011; 8321: 83211T-6.

Srinivas N, Deb K. Multiobjective Function Optimization Using Nondominated Sorting Genetic Algorithms, IEEE Transactions on Evolutionary Computation 1994; 2(3): 1301-08.

Wiangtong T, Cheung PYK, Luk W. Tabu Search with Intensification Strategy for Functional Partitioning in Hardware-Software Codesign, Field -Programmable Custom Computing Machines 2002; (4): 297-98.

Yang XS, Deb S. Cuckoo Search via Lévy flights, World Congress on Nature & Biologically Inspired Computing, IEEE 2009: 210-14.

Yang XS, Deb S. Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation 2010; 1(4): 330-43.

Yang XS. Engineering optimisation: An introduction with metaheuristic applications, John Wiley and Sons, 2010.

Zhang LB, Zhou CG, Liu XH, Ma ZQ, Liang YC. Solving multiobjective optimization problems using particle swarm optimization, Proceedings of the 2003 congress on evolutionary computation CEC2003, Canberra Australia: IEEE Press 2003; 2400-05.

Zhang Y, Luo W, Zhang Z, Li B, Wang X. A hardware/software partitioning algorithm based on artificial immune principles. Applied Soft Computing 2008; 8(1): 383-91.

Supporting Agencies

| NeuroScience + QuantumPhysics> NeuroQuantology :: Copyright 2001-2018