원문정보
초록
영어
As to the high request of low power consumption for hardware/software partitioning algorithm in multi-core processor structure, based on reducing the system power consumption, the relevant formal model was defined, and the problem was decomposed into two periods: the task division of heterogeneous multi-core platform and low power scheduling. The quantum genetic algorithm was proposed in the paper by taking the advantage of quantum computing combined with the traditional genetic algorithm, and the scheduling method based on critical tasks was used to solve scheduling problems of task after division. Experimental results show that the quantum genetic algorithm increases the diversity of population in the process of task partitioning and the task scheduling algorithm based on the key tasks determines the optimal execution order. The whole algorithm achieves the design goals of reducing the power consumption of the system and lessening the time complexity.
목차
1. Introduction
2. Hardware/software Partitioning Model
2.1. Target System Structure Model
2.2. Task Model
3. Quantum Genetic Algorithm
3.1. Qubits Encoded:
3.2. Update of Quantum Genetic Operations
3.3. Quantum Genetic Algorithm
4. Scheduling Algorithm based on Key Tasks
5. Experimental Results
6. Conclusion
Acknowledgements
References