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Modeling Execution Time of Selected Computation and Communication Kernels on Grids

  • Conference paper
Advances in Grid Computing - EGC 2005 (EGC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3470))

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Abstract

This paper introduces a methodology to model the execution time of several computation and communication routines developed in the frame of the CrossGrid project. The purpose of the methodology is to provide performance information about some selected computational kernels when they are executed in a grid. The models are based on analytical expressions obtained from exhaustive monitorized measurements. Even though the kernels that are considered in this work include both applications dependent and general purpose, the methodology can be applied to any kind of kernel in which the most relevant part in terms of execution time is due to computations and/or communications. We focused on MPI-based communications. In addition, an interactive Graphical User Interface was developed to summarize and show the information provided by the models from different views.

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References

  1. Simmons, M., Koskela, R.: Performance instrumentation and visualization. ACM Press, New York (1990)

    Google Scholar 

  2. Ajmone, M., balbo, G., Conte, G.: A class of generalized stochastic Petri nets for the performance analysis of multiprocessor systems. ACM trans. Computer Systems 2, 93–122 (1984)

    Article  Google Scholar 

  3. Gotz, N., Herzog, U., rettelbach, M.: Multiprocessor and distributed system design: the integration of functional specification and performance analysis using stochastic process algebras. In: Proc. SIGMETICS 1993 (1993)

    Google Scholar 

  4. Adve, V.S.: Analyzing the behavior and performance of parallel programs. PhD thesis. Techn. Report 1201. Ini. Of Wisconsin (1993)

    Google Scholar 

  5. Mak, V., Lundstrom, S.: Predicting performance of parallel computations. IEEE trans. Parallel and distributed systems 1, 253–270 (1990)

    Article  Google Scholar 

  6. Valiant, L.: A bridging model for parallel computations. Comm. ACM 33, 103–111 (1990)

    Article  Google Scholar 

  7. Culler, D., et al.: LogP: towards a realistic model of parallel computations. Proc. 4th ACM SIGPLAN symp., 1–12 (1993)

    Google Scholar 

  8. Fahringer, T.: Estimating and optimizing performance for parallel programs. Computer, 47–56 (November 1995)

    Google Scholar 

  9. Mendes, C., reed, D.: Integrated compilation and scalability analysis for parallel systems. Proc. Int. Conf. Parallel Architectures and Compiler Technology, 385–392 (1998)

    Google Scholar 

  10. Kerbyson, D.J., Papaefstatuiou, E., Harper, J.S., Perry, S.C., Nudd, G.R.: Is Predictive Tracing too late for HPC Users? In: Allan, R.J., Guest, M.F., Henty, D.S., Nicole, D., Simpson, A.D. (eds.) High Performance Computing” Proc. HPCI 1998 Conference 1998, pp. 57–67. Plenum/Kluwer Publishing, Dordrecht (1999)

    Google Scholar 

  11. Hey, T., Dunlop, A., Hernandez, E.: Realistic Parallel Performance Estimation. Parallel Computing 23, 5–21 (1997)

    Article  MATH  Google Scholar 

  12. DIMEMAS, http://www.pallas.de/pages/dimemas.htm

  13. Kubota, K., Itakura, K., Sato, M., Boku, T.: Practical Simulation of large-scale Parallel Programs and its Performance Analysis of the NAS Parallel Benchmarks. In: Pritchard, D., Reeve, J.S. (eds.) Euro-Par 1998. LNCS, vol. 1470, p. 244. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  14. Carnival, http://www.cs.rochester.edu/u/leblanc/prediction.html

  15. Kitajima, J.P., Tron, C., Plateau, B.: ALPES: a Tool for Performance Evaluation of Parallel Programs. In: Dongarra, J.J., Tourancheau, B. (eds.) Environnments and Tools for Parallel Scientific Computing, pp. 213–28. North-Holland, Amsterdam (1993)

    Google Scholar 

  16. Fahringer Estimating and optimising performance from parallel programs. special issue IEEE Computer 28, pp. 47-56 (1995)

    Google Scholar 

  17. Perfore, http://ParaMount.www.ecn.purdue.edu

  18. Bricks, http://www.is.ocha.ac.jp/takefusa/bricks/

  19. Hui, C.-C., Hamdi, M., Ahmad, I.: SPEED: A Parallel Platform for Solving and Predicting the Performance of PDEs on Distributed Systems Concurrency. Practice and Experience 9, 537–568 (1996)

    Article  Google Scholar 

  20. Miller, M., Hansen, C.D., Johnson, C.R.: Simulated Steering with SCIRun in a Distributed Environment. In: Kågström, B., Elmroth, E., Waśniewski, J., Dongarra, J. (eds.) PARA 1998. LNCS, vol. 1541, pp. 366–376. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  21. PARAISO, http://www.ac.usc.es/paraiso

  22. AlpStone, www.ifi.unibas.ch/generate.doc/English/Research/ParProg/alpstone/doc.html

  23. DAMIEN, http://www.hlrs.de/organization/pds/projects/damien/

  24. CrossGrid project, http://www.eu-crossgrid.org/

  25. PAPI, http://icl.cs.utk.edu/papi/

  26. JIMS, http://wp3.crossgrid.org/

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Author information

Authors and Affiliations

  1. Dept. Electronics and Computing, Univ. Santiago de Compostela, Spain

    M. Boullón, J. C. Cabaleiro, D. R. Martínez, T. F. Pena & F. F. Rivera

  2. Dept. Electronics and Systems, Univ. A Coruña, Spain

    R. Doallo, P. González, M. Martín & J. C. Mouriño

Authors
  1. M. Boullón
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  2. J. C. Cabaleiro
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  3. R. Doallo
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  4. P. González
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  5. D. R. Martínez
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  6. M. Martín
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  7. J. C. Mouriño
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  8. T. F. Pena
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  9. F. F. Rivera
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Editor information

Editors and Affiliations

  1. Faculty of Sciences, Section of Computational Science, University of Amsterdam, Kruislaan 403, 1098, Amsterdam, SJ, The Netherlands

    Peter M. A. Sloot

  2. Section Computational Science, University of Amsterdam, The Netherlands

    Alfons G. Hoekstra

  3. INRIA Rennes - Bretagne Atlantique, Campus de Beaulieu, 35042, Rennes Cedex, France

    Thierry Priol

  4. Zuse Institute Berlin,  

    Alexander Reinefeld

  5. Institute of Computer Science, AGH, Poland

    Marian Bubak

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© 2005 Springer-Verlag Berlin Heidelberg

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Boullón, M. et al. (2005). Modeling Execution Time of Selected Computation and Communication Kernels on Grids. In: Sloot, P.M.A., Hoekstra, A.G., Priol, T., Reinefeld, A., Bubak, M. (eds) Advances in Grid Computing - EGC 2005. EGC 2005. Lecture Notes in Computer Science, vol 3470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11508380_74

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  • DOI: https://doi.org/10.1007/11508380_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26918-2

  • Online ISBN: 978-3-540-32036-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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