Skip to main content
Log in

A mathematical model and a metaheuristic approach for a memory allocation problem

  • Published:
Journal of Heuristics Aims and scope Submit manuscript

Abstract

Memory allocation in embedded systems is one of the main challenges that electronic designers have to face. This part, rather difficult to handle is often left to the compiler with which automatic rules are applied. Nevertheless, an optimal allocation of data to memory banks may lead to great savings in terms of running time and energy consumption. This paper introduces an exact approach and a vns-based metaheuristic for addressing a memory allocation problem. Numerical experiments have been conducted on real instances from the electronic community and on dimacs instances expanded for our specific problem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Atienza, D., Mamagkakis, S., Poletti, F., Mendias, J., Catthoor, F., Benini, L., Soudris, D.: Efficient system-level prototyping of power-aware dynamic memory managers for embedded systems. Integration 39(2), 113–130 (2006)

    Google Scholar 

  • Battiti, R.: The reactive tabu search. ORSA J. Comput. 6, 126–140 (1994)

    MATH  Google Scholar 

  • Black, P.E.: Greedy algorithm. Dictionary of Algorithms and Data Structures, U.S. National Institute of Standards and Technology (2005)

  • Bouygues e-lab Innovation & Optimisation. Localsolver 1.0 (2010). http://e-lab.bouygues.com/?p=693

  • Carlson, R.C., Nemhauser, G.L.: Scheduling to minimize interaction cost. Oper. Res. 14(1), 52–58 (1966)

    Article  MathSciNet  MATH  Google Scholar 

  • Chiarandini, M., Paquete, A., Preuss, M., Ridge, E.: Experiments on metaheuristics: Methodological overview and open issues. Technical Report DMF-2007-03-003, The Danish Mathematical Society, Denmark (2007)

  • Chimientia, A., Fanucci, L., Locatellic, R., Saponarac, S.: VLSI architecture for a low-power video codec system. Microelectron. J. 33(5), 417–427 (2002)

    Article  Google Scholar 

  • Conover, W.J.: Practical Nonparametric Statistic, 3rd edn. Wiley, New York (1999)

    Google Scholar 

  • Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Greedy algorithms. In: Introduction to Algorithms, 2nd edn., pp. 370–404. MIT Press, Cambridge (1990)

    Google Scholar 

  • Coussy, P., Casseau, E., Bomel, P., Baganne, A., Martin, E.: A formal method for hardware IP design and integration under I/O and timing constraints. ACM Trans. Embed. Comput. Syst. 5(1), 29–53 (2006)

    Article  Google Scholar 

  • Diestel, R.: Graph Theory. Graduate Texts in Mathematics, vol. 173. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  • FICO. Xpress-MP (2009). http://www.dashoptimization.com/

  • Friedman, M.: The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J. Am. Stat. Assoc. 32, 675–701 (1937)

    Article  Google Scholar 

  • Glover, F., Laguna, M.: Tabu Search. Kluwer Academic, Dordrecht (1997)

    Book  MATH  Google Scholar 

  • GNU. GLPK linear programming kit (2009). http://www.gnu.org/software/glpk/

  • Herz, A., de Werra, D.: Using tabu search techniques for graph coloring. Computing 39(4), 345–351 (1987)

    Article  MathSciNet  Google Scholar 

  • Iverson, M., Ozguner, F., Potter, L.: Statistical prediction of task execution times through analytic benchmarking for scheduling in a heterogeneous environment. IEEE Trans. Comput. 48(12), 1374–1379 (1999)

    Article  Google Scholar 

  • Julien, N., Laurent, J., Senn, E., Martin, E.: Power consumption modeling and characterization of the TI C6201. IEEE MICRO 23(5), 40–49 (2003)

    Article  Google Scholar 

  • Kolen, A.W.J., Lenstra, J.K.: Combinatorics in operations research. In: Handbook of Combinatorics, pp. 1875–1910. Elsevier, Amsterdam (1995)

    Google Scholar 

  • Lee, W., Chang, M.: A study of dynamic memory management in C++ programs. Comput. Lang. Syst. Struct. 28(3), 237–272 (2002)

    Article  MATH  Google Scholar 

  • Mladenović, N., Hansen, P.: Variable neighbourhood decomposition search. Comput. Oper. Res. 24(11), 1097–1100 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  • Porumbel, D.: DIMACS graphs: Benchmark instances and best upper bound (2009). http://www.info.univ-angers.fr/pub/porumbel/graphs/

  • Porumbel, D., Hao, J.-K., Kuntz, P.: Diversity control and multi-parent recombination for evolutionary graph coloring algorithms. In: Proc. of the 9th EvoCOP Conference on Evolutionary Computation in Combinatorial Optimization, Tübingen, Germany, pp. 121–132 (2009)

    Chapter  Google Scholar 

  • Rego, C., Glover, F.: Local search and metaheuristics. In: Du, D.-Z., Pardalos, P.M., Gutin, G., Punnen, A. (eds.) The Traveling Salesman Problem and Its Variations. Combinatorial Optimization, vol. 12, pp. 309–368. Springer, Berlin (2004)

    Chapter  Google Scholar 

  • Soto, M., Rossi, A., Sevaux, M.: Two upper bounds on the chromatic number. In: Proc. of the CTW09 Cologne-Twente Workshop on Graphs and Combinatorial Optimization, Paris, France, vol. 8, pp. 191–194 (2009)

    Google Scholar 

  • Soto, M., Rossi, A., Sevaux, M.: Métaheuristiques pour l’allocation de mémoire dans les systèmes embarqués. In: Proc. ROADEF 11eme Congrès de la Société Française de Recherche Opérationelle et d’Aide à la Décision, Toulouse, France, pp. 35–43 (2010)

    Google Scholar 

  • Vredeveld, T., Lenstra, J.K.: On local search for the generalized graph coloring problem. Oper. Res. Lett. 31(1), 28–34 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  • Wuytack, S., Catthoor, F., Nachtergaele, L., De Man, H.: Power exploration for data dominated video application. In: Proc. IEEE Symposium on Low Power Design, Monterey, CA, USA, pp. 359–364 (1996)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marc Sevaux.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Soto, M., Rossi, A. & Sevaux, M. A mathematical model and a metaheuristic approach for a memory allocation problem. J Heuristics 18, 149–167 (2012). https://doi.org/10.1007/s10732-011-9165-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10732-011-9165-3

Keywords

Navigation