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Volume 19 (2022)
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Advances in Computer Science and Engineering
Advances in Computer Science and Engineering
Volume 1, Issue 3, Pages 249 - 261 (November 2007)
MULTI-OBJECTIVE GENETIC ALGORITHM FOR HARDWARE-SOFTWARE PARTITIONING IN EMBEDDED SYSTEMS: A WEIGHTED-SUM APPROACH
M. Jagadeeswari (India) and M. C. Bhuvaneswari (India)
Abstract:
This paper describes a novel weighted-sum genetic algorithm (WSGA) applied to hardware-software partitioning of embedded system design, where the traditional genetic algorithm (GA) can be customized to accommodate multi-objective problems by using specialized fitness functions. Genetic algorithms are popular meta-heuristic that is particularly well-suited for this class of problems because of population based approach. This method scalarizes a set of objectives into a single objective by pre-multiplying each objective with a user-supplied weight, which is chosen in proportion to the objectives relative importance in the problem. The time component of the system was also minimized by varying hardware area constraint on the hardware partition. These approaches generate superior results and execute much faster for larger systems and automatically generate a hardware/software partition with an objective to minimize the performance time. Finally a multi-objective optimization strategy was applied to search for multiple optimal solutions, the knowledge of which helps the designer to compare and choose a compromised optimal solution for which hardware/software design can be implemented. This method also promotes solution diversity than other heuristic approaches.
Keywords and phrases:
embedded systems, hardware-software partitioning, fitness function, weighted-sum genetic algorithm.
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P-ISSN: 0973-6999
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