A hardware/software partitioning algorithm based on artificial immune principles

Authors:
Yiguo Zhang;Wenjian Luo;Zeming Zhang;Bin Li;Xufa Wang
Affiliations:
Nature Inspired Computation and Applications Laboratory, Department of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China and Anhui Key Laboratory ...;Nature Inspired Computation and Applications Laboratory, Department of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China and Anhui Key Laboratory ...;Nature Inspired Computation and Applications Laboratory, Department of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China and Anhui Key Laboratory ...;Anhui Key Laboratory of Software in Computing and Communication, University of Science and Technology of China, Hefei 230027, China;Nature Inspired Computation and Applications Laboratory, Department of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China and Anhui Key Laboratory ...
Venue:
Applied Soft Computing
Year:
2008

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Abstract

Hardware/software codesign is the main approach to designing the embedded systems. One of the primary steps of the hardware/software codesign is the hardware/software partitioning. A good partitioning scheme is a tradeoff of some constraints, such as power, size, performance, and so on. Inspired by both negative selection model and evolutionary mechanism of the biological immune system, an evolutionary negative selection algorithm for hardware/software partitioning, namely ENSA-HSP, is proposed in this paper. This ENSA-HSP algorithm is proved to be convergent, and its ability to escape from the local optimum is also analyzed. The experimental results demonstrate that ENSA-HSP is more efficient than traditional evolutionary algorithm.