Two Iterative Metaheuristic Approaches to Dynamic Memory Allocation for Embedded Systems

  • María Soto
  • André Rossi
  • Marc Sevaux
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6622)

Abstract

Electronic embedded systems designers aim at finding a trade-off between cost and power consumption. As cache memory management has been shown to have a significant impact on power consumption, this paper addresses dynamic memory allocation for embedded systems with a special emphasis on time performance. In this work, time is split into time intervals, into which the application to be implemented by the embedded system requires accessing to data structures. The proposed iterative metaheuristics aim at determining which data structure should be stored in cache memory at each time interval in order to minimize reallocation and conflict costs. These approaches take advantage of metaheuristics previously designed for a static memory allocation problem.

Keywords

Memory allocation Electronics Metaheuristics 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    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 Transactions on Embedded Computing System 5(1), 29–53 (2006)CrossRefGoogle Scholar
  2. 2.
    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, the VLSI Journal 39(2), 113–130 (2006)CrossRefGoogle Scholar
  3. 3.
    Chimientia, A., Fanucci, L., Locatellic, R., Saponarac, S.: VLSI architecture for a low-power video codec system. Microelectronics Journal 33(5), 417–427 (2002)CrossRefGoogle Scholar
  4. 4.
    Julien, N., Laurent, J., Senn, E., Martin, E.: Power consumption modeling and characterization of the TI C6201. IEEE Micro. 23(5), 40–49 (2003)CrossRefGoogle Scholar
  5. 5.
    Wuytack, S., Catthoor, F., Nachtergaele, L., Man, H.D.: Power exploration for data dominated video application. In: Proc. IEEE International Symposium on Low Power Electronics and Design, Monterey, CA, USA, pp. 359–364 (1996)Google Scholar
  6. 6.
    Cho, D., Pasricha, S., Issenin, I., Dutt, N.D., Ahn, M., Paek, Y.: Adaptive scratch pad memory management for dynamic behavior of multimedia applications. Trans. Comp.-Aided Des. Integ. Cir. Sys. 28, 554–567 (2009)CrossRefGoogle Scholar
  7. 7.
    Ozturk, O., Kandemir, M., Irwin, M.J.: Using data compression for increasing memory system utilization. Trans. Comp.-Aided Des. Integ. Cir. Sys. 28, 901–914 (2009)CrossRefGoogle Scholar
  8. 8.
    Soto, M., Rossi, A., Sevaux, M.: Exact and metaheuristic approaches for a memory allocation problem. In: Proc. EU/MEeting, Workshop on the Metaheuristics Community, Lorient, France, pp. 25–29 (2010)Google Scholar
  9. 9.
    Iverson, M., Ozguner, F., Potter, L.: Statistical prediction of task execution times through analytic benchmarking for scheduling in a heterogeneous environment. IEEE Transactions on Computers 48(12), 1374–1379 (1999)CrossRefGoogle Scholar
  10. 10.
    Lee, W., Chang, M.: A study of dynamic memory management in C++ programs. Comp. Languages Systems and Structures 28(3), 237–272 (2002)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Softexplorer (2006), [Online] http://www.softexplorer.fr/
  12. 12.
    Xpress-mp, FICO (2009), [Online] http://www.dashoptimization.com/
  13. 13.
    Carlson, R., Nemhauser, G.: Scheduling to minimize interation cost. Operations Research 14, 52–58 (1966)MathSciNetCrossRefMATHGoogle Scholar
  14. 14.
    Besbes, S.F.J.H.: A solution to reduce noise enhancement in pre-whitened lms-type algorithms: the double direction adaptation. In: Proc. Control, Communications and Signal Processing, 2004, pp. 717–720 (2004)Google Scholar
  15. 15.
    Herz, A., de Werra, D.: Using tabu search techniques for graph coloring. Computing 39(4), 345–351 (1987)MathSciNetCrossRefMATHGoogle Scholar
  16. 16.
    Battiti, R.: The reactive tabu search. ORSA Journal on Computing 6(2), 126–140 (1994)CrossRefMATHGoogle Scholar
  17. 17.
    Porumbel, D., Hao, J.-K., Kuntz, P.: Diversity control and multi-parent recombination for evolutionary graph coloring algorithms. In: Cotta, C., Cowling, P. (eds.) EvoCOP 2009. LNCS, vol. 5482, pp. 121–132. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  18. 18.
    Porumbel, D.: DIMACS graphs: Benchmark instances and best upper bound (2009), [Online] http://www.info.univ-angers.fr/pub/porumbel/graphs/

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • María Soto
    • 1
  • André Rossi
    • 1
  • Marc Sevaux
    • 1
  1. 1.Lab-STICC, CNRSUniversité de Bretagne-SudLorient CedexFrance

Personalised recommendations