Abstract
The need for inexpensive, compact and adaptive systems has seen accelerated interest in the codesign of embedded systems. The ability to estimate the acceleration obtainable is highly desirable, as time to market deadlines are being ever shortened. The performance of such systems is fundamentally dependent on the hardware-software (HW-SW) partition. In this paper a genetic algorithm-based hardware-software partitioning method is presented. Demonstrative applications are used to show the effectiveness of the genetic algorithm at exploiting the reconfigurable nature of such systems.
Keywords
- Fitness Evaluation
- Dynamic Reconfiguration
- Reconfigurable Hardware
- Partial Reconfiguration
- Reconfiguration Time
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2001 Springer-Verlag Berlin Heidelberg
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Harkin, J., McGinnity, T.M., Maguire, L.P. (2001). Hardware-Software Partitioning: A Reconfigurable and Evolutionary Computing Approach. In: Brebner, G., Woods, R. (eds) Field-Programmable Logic and Applications. FPL 2001. Lecture Notes in Computer Science, vol 2147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44687-7_62
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DOI: https://doi.org/10.1007/3-540-44687-7_62
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