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.

System Level Hardware--Software Design Exploration with XCS

FERRANDI, FABRIZIO;LANZI, PIER LUCA;SCIUTO, DONATELLA
2004-01-01

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.
2004
Genetic and Evolutionary Computation -- GECCO 2004: Genetic and Evolutionary Computation Conference, Seattle, WA, USA, June 26-30, 2004. Proceedings, Part II
9783540223436
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/268312
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