Abstract
The current trend in Embedded Systems (ES) design is moving towards the integration of increasingly complex applications on a single chip. An Embedded System has to satisfy both performance constraints and cost limits; it is composed of both dedicated elements, i.e. hardware (HW) components, and programmable units, i.e. software (SW) components, Hardware (HW) and software (SW) components have to interact with each other for accomplishing a specific task. One of the aims of codesign is to support the exploration of the most significant architectural alternatives in terms of decomposition between hardware (HW) and software (SW) components. In this paper, we propose a novel approach to support the exploration of feasible hardware-software (HW-SW) configurations. The approach exploits the learning classifier system XCS both to identify existing relationships among the system components and to support HW-SW partitioning decisions. We validate the approach by applying it to the design of a Digital Sound Spatializer.KeywordsExecution TimeEmbed SystemVery Large Scale IntegrationLearning Classifier SystemData Flow GraphThese 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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