Abstract
In this paper we present a multi-objective genetic algorithm to solve the problem of mapping a set of task graphs onto a heterogeneous multiprocessor platform. The objective is to meet all real-time deadlines subject to minimizing system cost and power consumption, while staying within bounds on local memory sizes and interface buffer sizes. Our approach allows for mapping onto a fixed platform or onto a flexible platform where architectural changes are explored during the mapping.
We demonstrate our approach through an exploration of a smart phone, where five task graphs with a total of 530 tasks after hyper period extension are mapped onto a multiprocessor platform. The results show four non-inferior solutions which tradeoffs the various objectives.
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Keywords
- Schedule Algorithm
- Task Graph
- Design Space Exploration
- Multiobjective Genetic Algorithm
- Multiprocessor Platform
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© 2006 International Federation for Information Processing
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Madsen, J., Stidsen, T.K., Kjaerulf, P., Mahadevan, S. (2006). Multi-Objective Design Space Exploration of Embedded System Platforms. In: Kleinjohann, B., Kleinjohann, L., Machado, R.J., Pereira, C.E., Thiagarajan, P.S. (eds) From Model-Driven Design to Resource Management for Distributed Embedded Systems. DIPES 2006. IFIP International Federation for Information Processing, vol 225. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39362-9_20
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DOI: https://doi.org/10.1007/978-0-387-39362-9_20
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-39361-2
Online ISBN: 978-0-387-39362-9
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