Skip to main content
Springer Nature Link
Log in

MPI to Go: Container Clusters for MPI Applications

  • Conference paper
  • First Online:
Cloud Computing and Services Science (CLOSER 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1218))

Included in the following conference series:

  • 529 Accesses

Abstract

Container-based virtualization has been investigated as an attractive solution to achieve isolation, flexibility and efficiency in a wide range of computational applications. In High Performance Computing, many applications rely on clusters to run multiple communicating processes using MPI (Message Passing Interface) communication protocol. Container clusters based on Docker Swarm or Kubernetes may bring benefits to HPC scenarios, but deploying MPI applications over such platforms is a challenging task. In this work, we propose a self-content Docker Swarm platform capable of supporting MPI applications, and validate it though the performance characterization of a meteorological scientific application.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
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

Similar content being viewed by others

Notes

  1. 1.

    https://www.docker.com/.

  2. 2.

    https://hub.docker.com/.

  3. 3.

    https://blog.hypriot.com/.

  4. 4.

    https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/dgx-1/dgx-1-rhel-centos-datasheet-update-r2.pdf.

  5. 5.

    https://github.com/lsteffenel/swarm_mpi_basic.

  6. 6.

    http://meso.univ-reims.fr.

  7. 7.

    https://github.com/lsteffenel/wrf-container-armv7l-RaspberryPi.

  8. 8.

    http://vite.gforge.inria.fr/.

  9. 9.

    https://vampir.eu/.

References

  1. Ali, M., Vlaskamp, J.H.A., Eddin, N.N., Falconer, B., Oram, C.: Technical development and socioeconomic implications of the Raspberry Pi as a learning tool in developing countries. In: Computer Science and Electronic Engineering Conference (CEEC), pp. 103–108. IEEE (2013)

    Google Scholar 

  2. Alvarez, L., Ayguade, E., Mantovani, F.: Teaching HPC systems and parallel programming with small-scale clusters. In: 2018 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC), pp. 1–10, November 2018. https://doi.org/10.1109/EduHPC.2018.00004

  3. Azab, A.: Enabling Docker containers for high-performance and many-task computing. In: 2017 IEEE International Conference on Cloud Engineering (IC2E), pp. 279–285, April 2017. https://doi.org/10.1109/IC2E.2017.52

  4. Barker, D.: Setting up an ARM-based micro-cluster and running the WRF weather model, March 2014. http://supersmith.com/site/ARM.html

  5. de Bayser, M., Cerqueira, R.: Integrating MPI with Docker for HPC. In: 2017 IEEE International Conference on Cloud Engineering (IC2E), pp. 259–265, April 2017. https://doi.org/10.1109/IC2E.2017.40

  6. Beserra, D., Pinheiro, M.K., Souveyet, C., Steffenel, L.A., Moreno, E.D.: Performance evaluation of OS-level virtualization solutions for HPC purposes on SOC-based systems. In: 2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA), pp. 363–370, March 2017. https://doi.org/10.1109/AINA.2017.73

  7. Burns, B., Grant, B., Oppenheimer, D., Brewer, E., Wilkes, J.: Borg, omega, and kubernetes. Commun. ACM 59(5), 50–57 (2016). https://doi.org/10.1145/2890784

    Article  Google Scholar 

  8. Chung, M.T., Quang-Hung, N., Nguyen, M., Thoai, N.: Using docker in high performance computing applications. In: 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE), pp. 52–57, July 2016. https://doi.org/10.1109/CCE.2016.7562612

  9. HPC Advisory Council: Weather research and forecasting (WRF): performance benchmark and profiling, best practices of the HPC advisory council. Technical report, HPC Advisory Council (2010). http://www.hpcadvisorycouncil.com/pdf/WRF_Analysis_and_Profiling_Intel.pdf

  10. Cox, S.J., Cox, J.T., Boardman, R.P., Johnston, S.J., Scott, M., O’brien, N.S.: Iridis-pi: a low-cost, compact demonstration cluster. Cluster Comput. 17(2), 349–358 (2014). https://doi.org/10.1007/s10586-013-0282-7

    Article  Google Scholar 

  11. Docker Inc.: Use swarm mode routing mesh. https://docs.docker.com/engine/swarm/ingress/

  12. Felter, W., Ferreira, A., Rajamony, R., Rubio, J.: An updated performance comparison of virtual machines and Linux containers. IBM technical report RC25482 (AUS1407-001), Computer Science (2014)

    Google Scholar 

  13. Higgins, J., Holmes, V., Venters, C.: Orchestrating docker containers in the HPC environment. In: Kunkel, J.M., Ludwig, T. (eds.) ISC High Performance 2015. LNCS, vol. 9137, pp. 506–513. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20119-1_36

    Chapter  Google Scholar 

  14. Iveson, S.: TCP/IP over VXLAN bandwidth overheads, March 2014. https://packetpushers.net/vxlan-udp-ip-ethernet-bandwidth-overheads/

  15. Joy, A.M.: Performance comparison between Linux containers and virtual machines. In: International Conference on Advances in Computer Engineering and Applications (ICACEA), pp. 342–346. IEEE (2015)

    Google Scholar 

  16. Kurtzer, G.M., Sochat, V., Bauer, M.W.: Singularity: scientific containers for mobility of compute. PLoS ONE 12(5), 1–20 (2017). https://doi.org/10.1371/journal.pone.0177459

    Article  Google Scholar 

  17. Langkamp, T., Böhner, J.: Influence of the compiler on multi-CPU performance of WRFv3. Geosci. Model Dev. 4(3), 611–623 (2011). https://doi.org/10.5194/gmd-4-611-2011. https://www.geosci-model-dev.net/4/611/2011/

    Article  Google Scholar 

  18. Manohar, N.: A survey of virtualization techniques in cloud computing. In: Chakravarthi, V., Shirur, Y., Prasad, R. (eds.) VCASAN-2013. LNEE, vol. 258, pp. 461–470. Springer, Cham (2013). https://doi.org/10.1007/978-81-322-1524-0_54

    Chapter  Google Scholar 

  19. Molano, J.I.R., Betancourt, D., Gómez, G.: Internet of Things: a prototype architecture using a Raspberry Pi. In: Uden, L., Heričko, M., Ting, I.-H. (eds.) KMO 2015. LNBIP, vol. 224, pp. 618–631. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-21009-4_46

    Chapter  Google Scholar 

  20. Montella, R., Giunta, G., Laccetti, G.: Virtualizing high-end GPGPUS on ARM clusters for the next generation of high performance cloud computing. Cluster Comput. 17(1), 139–152 (2014). https://doi.org/10.1007/s10586-013-0341-0

    Article  Google Scholar 

  21. MPI Forum: MPI: A message-passing interface standard version 3.1. https://www.mpi-forum.org/docs/

  22. Nguyen, N., Bein, D.: Distributed MPI cluster with Docker Swarm mode. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pp. 1–7, January 2017. https://doi.org/10.1109/CCWC.2017.7868429

  23. Ruiz, C., Jeanvoine, E., Nussbaum, L.: Performance evaluation of containers for HPC. In: HunoldHunold, S., et al. (eds.) Euro-Par 2015. LNCS, vol. 9523, pp. 813–824. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-27308-2_65

    Chapter  Google Scholar 

  24. Skamarock, W.C., et al.: A description of the advanced research WRF version 3. NCAR technical note. National Center for Atmospheric Research, Boulder, Colorado, USA (2008)

    Google Scholar 

  25. Somasundaram, T.S., Govindarajan, K.: CLOUDRB: a framework for scheduling and managing High-Performance Computing (HPC) applications in science cloud. Future Gen. Comput. Syst. 34, 47–65 (2014)

    Article  Google Scholar 

  26. Steffenel, L.A., Kirsch Pinheiro, M.: When the cloud goes pervasive: approaches for IoT PaaS on a mobiquitous world. In: Mandler, B., et al. (eds.) IoT360 2015. LNICST, vol. 169, pp. 347–356. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47063-4_36

    Chapter  Google Scholar 

  27. Steffenel., L.A., Charão., A.S., da Silva Alves., B.: A containerized tool to deploy scientific applications over SOC-based systems: the case of meteorological forecasting with WRF. In: Proceedings of the 9th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, pp. 561–568. INSTICC, SciTePress (2019). https://doi.org/10.5220/0007799705610568

  28. Trahay, F., Rue, F., Faverge, M., Ishikawa, Y., Namyst, R., Dongarra, J.: EZTrace: a generic framework for performance analysis. In: 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 618–619. IEEE (2011)

    Google Scholar 

  29. Weloli, J.W., Bilavarn, S., Vries, M.D., Derradji, S., Belleudy, C.: Efficiency modeling and exploration of 64-bit ARM compute nodes for exascale. Microprocess. Microsyst. 53, 68–80 (2017). https://doi.org/10.1016/j.micpro.2017.06.019. http://www.sciencedirect.com/science/article/pii/S0141933116304537

    Article  Google Scholar 

  30. Wolf, W., Jerraya, A.A., Martin, G.: Multiprocessor system-on-chip (MPSoC) technology. IEEE Trans. Comput.-Aided Des. Integr. Circ. Syst. 27(10), 1701–1713 (2008)

    Article  Google Scholar 

  31. Xavier, M.G., Neves, M.V., Rossi, F.D., Ferreto, T.C., Lange, T., De Rose, C.A.F.: Performance evaluation of container-based virtualization for high performance computing environments. In: 2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, pp. 233–240, February 2013. https://doi.org/10.1109/PDP.2013.41

  32. Yong, C., Lee, G.W., Huh, E.N.: Proposal of container-based HPC structures and performance analysis. J. Inf. Process. Syst. 14(6), 1398–1404 (2018)

    Google Scholar 

  33. Younge, A.J., Henschel, R., Brown, J.T., von Laszewski, G., Qiu, J., Fox, G.C.: Analysis of virtualization technologies for high performance computing environments. In: IEEE 4th International Conference on Cloud Computing, CLOUD 2011, pp. 9–16. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

Download references

Acknowledgements

This research has been partially supported by the French-Brazilian CAPES-COFECUB MESO project (http://meso.univ-reims.fr) and the GREEN-CLOUD project (http://www.inf.ufrgs.br/greencloud/) (#16/2551-0000 488-9), from FAPERGS and CNPq Brazil, program PRONEX 12/2014.

Author information

Authors and Affiliations

  1. CREsTIC Laboratory, Université de Reims Champagne Ardenne, Reims, France

    Luiz Angelo Steffenel

  2. Universidade Federal de Santa Maria, Santa Maria, Brazil

    Andrea S. Charão, Bruno Alves, Lucas R. de Araujo & Lucas F. da Silva

Authors
  1. Luiz Angelo Steffenel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrea S. Charão
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bruno Alves
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lucas R. de Araujo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lucas F. da Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Luiz Angelo Steffenel .

Editor information

Editors and Affiliations

  1. Columbia University, New York, NY, USA

    Donald Ferguson

  2. Escola d’Enginyeria, Bellaterra, Barcelona, Spain

    Víctor Méndez Muñoz

  3. Free University of Bozen-Bolzano, Bolzano, Bolzano, Italy

    Claus Pahl

  4. Dublin City University, Dublin, Ireland

    Markus Helfert

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Steffenel, L.A., Charão, A.S., Alves, B., de Araujo, L.R., da Silva, L.F. (2020). MPI to Go: Container Clusters for MPI Applications. In: Ferguson, D., Méndez Muñoz, V., Pahl, C., Helfert, M. (eds) Cloud Computing and Services Science. CLOSER 2019. Communications in Computer and Information Science, vol 1218. Springer, Cham. https://doi.org/10.1007/978-3-030-49432-2_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-49432-2_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49431-5

  • Online ISBN: 978-3-030-49432-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics