원문정보
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초록
영어
As to the embedded system of multi-tasks, this paper proposes a hardware/software partitioning algorithm based on Clustering algorithm using reference and density and Genetic algorithm. The algorithm uses reference task to reflect attribute of system task node, and firstly finish classification of task nodes to decrease the scale of the system, and then partitions hardware/software based on genetic algorithm. The experiments results have showed that this algorithm can accelerate converge to appropriate solution of complex system with more tasks.
목차
Abstract
1. Introduction
2. Model of Hardware/Software Partitioning
2.1 Features of model
2.2 Description of Hardware/Software Partitioning
3. Partitioning Algorithm of Hardware/software
3.1 Clustering Algorithm
3.2 Combination of Clustering Algorithm and Genetic Algorithm
4. Experiment and Analysis
4.1 Experimental Samples and Experimental Environment
4.2 Parameter Setting
4.3 Experiment Comparison
5. Conclusion
Acknowledgements
References
1. Introduction
2. Model of Hardware/Software Partitioning
2.1 Features of model
2.2 Description of Hardware/Software Partitioning
3. Partitioning Algorithm of Hardware/software
3.1 Clustering Algorithm
3.2 Combination of Clustering Algorithm and Genetic Algorithm
4. Experiment and Analysis
4.1 Experimental Samples and Experimental Environment
4.2 Parameter Setting
4.3 Experiment Comparison
5. Conclusion
Acknowledgements
References
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자료제공 : 네이버학술정보