Steady-State for Batches of Identical Task Trees

  • Sékou Diakité
  • Loris Marchal
  • Jean-Marc Nicod
  • Laurent Philippe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5704)

Abstract

In this paper, we focus on the problem of scheduling batches of identical task graphs on a heterogeneous platform, when the task graph consists in a tree. We rely on steady-state scheduling, and aim at reaching the optimal throughput of the system. Contrarily to previous studies, we concentrate upon the scheduling of batches of limited size. We try to reduce the processing time of each instance, thus making steady-state scheduling applicable to smaller batches. The problem is proven NP-complete, and a mixed integer program is presented to solve it. Then, different solutions, using steady-state scheduling or not, are evaluated through comprehensive simulations.

Keywords

Schedule Algorithm Batch Size Task Graph Periodic Schedule Optimal Throughput 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Foster, I.T., Kesselman, C. (eds.): The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers, San Francisco (2004)Google Scholar
  2. 2.
    Chervenak, A., Foster, I., Kesselman, C., Salisbury, C., Tuecke, S.: The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets. Journal of Network and Computer Applications 23(3), 187–200 (2000)CrossRefGoogle Scholar
  3. 3.
    Oinn, T.M., Addis, M., Ferris, J., Marvin, D., Senger, M., Greenwood, R.M., Carver, T., Glover, K., Pocock, M.R., Wipat, A., Li, P.: Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics 20, 3045–3054 (2004)CrossRefGoogle Scholar
  4. 4.
    Germain, C., Breton, V., Clarysse, P., Gaudeau, Y., Glatard, T., Jeannot, E., Legré, Y., Loomis, C., Magnin, I., Montagnat, J., Moureaux, J.M., Osorio, A., Pennec, X., Texier, R.: Grid-enabling medical image analysis. Journal of Clinical Monitoring and Computing 19, 339–349 (2005)CrossRefGoogle Scholar
  5. 5.
    Lee, S., Cho, M.K., Jung, J.W., Weontae Lee, J.H.K.: Exploring protein fold space by secondary structure prediction using data distribution method on grid platform. Bioinformatics 20, 3500–3507 (2004)CrossRefGoogle Scholar
  6. 6.
    Pitt-Francis, J., Garny, A., Gavaghan, D.: Enabling computer models of the heart for high-performance computers and the grid. Philosophical Transactions of the Royal Society A 364, 1501–1516 (2006)CrossRefGoogle Scholar
  7. 7.
    Ludtke, S.J., Baldwin, P.R., Chiu, W.: EMAN: Semiautomated Software for High-Resolution Single-Particle Reconstructions. Journal of Structural Biology 128, 82–97 (1999)CrossRefGoogle Scholar
  8. 8.
    Peng, L., Candan, K.S., Mayer, C., Chatha, K.S., Ryu, K.D.: Optimization of media processing workflows with adaptive operator behaviors. In: Multimedia Tools and Applications. Computer Science, vol. 33, pp. 245–272. Springer, Heidelberg (2007)Google Scholar
  9. 9.
    Beaumont, O., Legrand, A., Marchal, L., Robert, Y.: Steady-state scheduling on heterogeneous clusters. Int. J. of Foundations of Computer Science 16, 163–194 (2005)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Bertsimas, D., Gamarnik, D.: Asymptotically optimal algorithms for job shop scheduling and packet routing. J. Algorithms 33, 296–318 (1999)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Diakité, S., Nicod, J.M., Philippe, L.: Comparison of batch scheduling for identical multi-tasks jobs on heterogeneous platforms. In: PDP, pp. 374–378 (2008)Google Scholar
  12. 12.
    Diakité, S., Marchal, L., Nicod, J.M., Philippe, L.: Steady-state for batches of identical task graphs. Research report RR2009-18, LIP, ENS Lyon, France (2009)Google Scholar
  13. 13.
    ILOG: Cplex: High-performance software for mathematical programming and optimization (1997), http://www.ilog.com/products/cplex/
  14. 14.
    Topcuoglu, H., Hariri, S., Wu, M.-Y.: Task scheduling algorithms for heterogeneous processors. In: Proceedings of HCW 1999, Washington, DC, USA, p. 3. IEEE CS, Los Alamitos (1999)Google Scholar
  15. 15.
    Casanova, H., Legrand, A., Quinson, M.: SimGrid: a Generic Framework for Large-Scale Distributed Experiments. In: 10th IEEE International Conference on Computer Modeling and Simulation (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sékou Diakité
    • 1
  • Loris Marchal
    • 2
  • Jean-Marc Nicod
    • 1
  • Laurent Philippe
    • 1
  1. 1.Laboratoire d’Informatique de Franche-ComtéUniversité de France ComtéFrance
  2. 2.Laboratoire de l’Informatique du Parallélisme CNRS - INRIAUniversité de LyonFrance

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