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Multi-objective optimization of multimedia embedded systems using genetic algorithms and stochastic simulation

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Abstract

To meet the ever shrinking time-to-market for multimedia embedded systems, designers need effective system-level optimization techniques to support their design decisions. Despite multimedia embedded systems’ highly variable execution times and soft real-time constraints, most previous work has adopted a constant execution time (worst-case) approach to evaluate if a candidate architecture satisfies the timing constraints. Such an approach is too pessimistic and might result in unnecessary costly architectures. In this work, we propose a new method for design space exploration of multimedia embedded systems. Given a system specification, the proposed method automatically explores the design space to quickly identify Pareto-optimal solutions (or an approximation) that optimize conflicting design metrics, such as price and power consumption. Our approach combines (i) a fast and formal strategy for performance evaluation that captures the varying runtime behavior of multimedia systems and (ii) a new multi-objective genetic algorithm for architecture exploration. The experiments on well-known benchmarks show the efficiency of our method in comparison to similar ones.

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Notes

  1. A bag (also known as multiset) is a set that allows duplicates.

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Authors and Affiliations

  1. Academic Unit of Garanhuns, Federal Rural University of Pernambuco, Garanhuns, Brazil

    Bruno Nogueira

  2. Center of Informatics, Federal University of Pernambuco, Recife, Brazil

    Paulo Maciel, Eduardo Tavares & Ricardo M. A. Silva

  3. Department of Statistics and Informatics, Federal Rural University of Pernambuco, Recife, Brazil

    Ermeson Andrade

Authors
  1. Bruno Nogueira
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  2. Paulo Maciel
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  3. Eduardo Tavares
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  4. Ricardo M. A. Silva
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  5. Ermeson Andrade
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Corresponding author

Correspondence to Bruno Nogueira.

Additional information

Communicated by V. Loia.

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Nogueira, B., Maciel, P., Tavares, E. et al. Multi-objective optimization of multimedia embedded systems using genetic algorithms and stochastic simulation. Soft Comput 21, 4141–4158 (2017). https://doi.org/10.1007/s00500-016-2061-x

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  • DOI: https://doi.org/10.1007/s00500-016-2061-x

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