Skip to main content

Improving Multilevel Approach for Optimizing Collective Communications in Computational Grids

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

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

Included in the following conference series:

Abstract

Collective operations represent a tool for easy implementation of parallel algorithms in the message-passing parallel programming languages. Efficient implementation of these operations significantly improves the performance of the parallel algorithms, especially in the Grid systems. We introduce an improvement of multilevel algorithm that enables improvement of the performance of collective communication operations. An implementation of the algorithm is used for analyzing its characteristics and for comparing its performance it with the multilevel algorithm.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers, San Francisco (1999)

    Google Scholar 

  2. Message Passing Interface Forum: MPI: A message-passing interface standard. International Journal of Supercomputer Applications 8(3/4), 165–414 (1994)

    Google Scholar 

  3. Vadhiyar, S.S., Fagg, G.E., Dongarra, J.: Automatically Tuned Collective Communications. In: Proceedings of the IEEE/ACM SC 2000 Conference, Dallas, Texas (2000)

    Google Scholar 

  4. Lowekamp, B.B., Beguelin, A.: ECO: Efficient Collective Operations for communication on heterogeneous networks. In: Proc. of 10th Intl. Parallel Processing Symposium, pp. 399–405 (1996)

    Google Scholar 

  5. Banikazemi, M., Moorthy, V., Panda, D.: Efficient Collective Communication on Heterogeneous Networks of Workstations. In: International Conference on Parallel Processing, Minneapolis, MN, pp. 460–467 (1998)

    Google Scholar 

  6. Bhat, P.B., Raghavendra, C.S., Prasanna, V.K.: Efficient Collective Communication in Distributed Heterogeneous Systems. In: Proceedings of the International Conference on Distributed Computing Systems (1999)

    Google Scholar 

  7. Cha, K., Han, D., Yu, C., Byeon, O.: Two-Tree Collective Communication in Distributed Heterogeneous Systems. In: IASTED International Conference on Networks, Parallel and Distributed Processing, and Applications (2002)

    Google Scholar 

  8. Kielmann, T., Hofman, R.F.H., Bal, H.E., Plaat, A., Bhoedjang, R.A.F.: MAGPIE: MPI’s Collective Communication Operations for Clustered Wide Area Systems. In: Proc. Symposium on Principles and Practice of Parallel Programming (PPoPP), Atlanta, GA, pp. 131–140 (1999)

    Google Scholar 

  9. Kielmann, T., Bal, H.E., Gorlatch, S.: Bandwidth-efficient Collective Communication for Clustered Wide Area Systems. In: Feitelson, D.G., Rudolph, L. (eds.) IPDPS-WS 2000 and JSSPP 2000. LNCS, vol. 1911. Springer, Heidelberg (2000)

    Google Scholar 

  10. Karonis, N., de Supinski, B., Foster, I., Gropp, W., Lusk, E., Bresnahan, J.: Exploiting hierarchy in parallel computer networks to optimize collective operation performance. In: Proc. of the 14th International Parallel and Distributed Processing Symposium, pp. 377–384 (2000)

    Google Scholar 

  11. MPICH-G2 web page, http://www.globus.org/mpi

  12. Culler, D.E., Karp, R., Patterson, D.A., Sahay, A., Schauser, K.E., Santos, E., Subramonian, R., von Eicken, T.: LogP: Towards a realistic model of parallel computation. In: Proceedings of the 4th SIGPLAN Symposium on Principles and Practices of Parallel Programming, pp. 1–12 (1993)

    Google Scholar 

  13. Bernaschi, M., Iannello, G.: Collective Communication Operations: Experimental Results vs. Theory. Concurrency: Practice and Experience 10(5), 359–386 (1998)

    Article  MATH  Google Scholar 

  14. de Supinski, B., Karonis, N.: Accurately Measuring MPI Broadcasts in a Computational Grid. In: The Eighth IEEE International Symposium on High Performance Distributed Computing. IEEE Computer Society Press, Los Alamitos (1999)

    Google Scholar 

  15. Lacour, S.: MPICH-G2 collective operations: performance evaluation, optimizations. Rapport de stage MIM2, Magistère d’informatique et modélisation (MIM), ENS Lyon, MCS Division, Argonne National Laboratory, USA (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jakimovski, B., Gusev, M. (2005). Improving Multilevel Approach for Optimizing Collective Communications in Computational 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_56

Download citation

  • DOI: https://doi.org/10.1007/11508380_56

  • 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)

Publish with us

Policies and ethics