Energy-Optimal Software Partitioning in Heterogeneous Multiprocessor Embedded Systems

Embedded systems with heterogeneous processors extend the energy/

timing trade-off flexibility and provide the opportunity to fine

tune resource utilization for particular applications. In this paper,

we present a resource model that considers the time and energy

costs of run-time mode switching, which considerably improves

the accuracy of existing models. Given an application, the software

partitioning problem then becomes an optimization over energy

cost given deadline constraints, which can be formulate as

an integer linear programming (ILP) problem. We apply the resource

modeling and software partitioning techniques to a multimodule

embedded sensing device, the mPlatform, and present a

case study of configuring the platform for a real-time sound source

localization application on a stack of MSP430 and ARM7 processor

based sensing and processing boards.

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In  The 45th Design Automation Conference (DAC 2008)

Publisher  Association for Computing Machinery, Inc.
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