Towards the Integration of a HPC Build System in the Cloud Ecosystem

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 611)


Once the Cloud computing matures, and the diversification of resources and levels at which they can be accessed, there is a growing need to identify specialized languages and technologies that can provide a high level of flexibility and transparency in accessing, managing, and utilizing these resources. In this context, the alignment of these capabilities with current developments, especially at topology, orchestration and management level, becomes a necessity. Such an implementation is usually based on a self-* approach, which is also suitable for supporting the migration of selected HPC applications to the cloud. Our research is based on a self-organizing, self-management approach and investigates the option of self-configuration, supported by the easybuild toolchain.


Cloud computing Easybuild Cloud orchestration 



This work was partially funded by the European Union’s Horizon 2020 Research and Innovation Programme through the CloudLightning project ( under Grant Agreement Number 643946.


  1. 1.
    Geada, D.: The case for the heterogeneous cloud. Cloud Comput. J. 11(3), 521–525 (2011)Google Scholar
  2. 2.
    Moscato, F., Aversa, R., Di Martino, B., Fortiş, T.F., Munteanu, V.: An analysis of mOSAIC ontology for cloud resources annotation. In: 2011 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 973–980. IEEE (2011)Google Scholar
  3. 3.
    Ferry, N., Almeida, M., Solberg, A.: The MODAClouds model-driven development. In: Model-Driven Development and Operation of Multi-Cloud Applications, pp. 23–33. Springer Nature, December 2016Google Scholar
  4. 4.
    Soldani, J., Binz, T., Breitenbcher, U., Leymann, F., Brogi, A.: ToscaMart: a method for adapting and reusing cloud applications. J. Syst. Softw. 113, 395–406 (2016)CrossRefGoogle Scholar
  5. 5.
    Sanaei, Z., Abolfazli, S., Gani, A., Buyya, R.: Heterogeneity in mobile cloud computing: taxonomy and open challenges. IEEE Commun. Surv. Tutorials 16(1), 369–392 (2014)CrossRefGoogle Scholar
  6. 6.
    Gupta, A., Kale, L.V., Gioachin, F., March, V., Suen, C.H., Lee, B.S., Faraboschi, P., Kaufmann, R., Milojicic, D.: The who, what, why, and how of high performance computing in the cloud. In: 2013 IEEE 5th International Conference on Cloud Computing Technology and Science. IEEE, December 2013Google Scholar
  7. 7.
    Somasundaram, T.S., Govindarajan, K.: CLOUDRB: a framework for scheduling and managing high-performance computing (HPC) applications in science cloud. Future Gener. Comput. Syst. 34, 47–65 (2014)CrossRefGoogle Scholar
  8. 8.
    Mauch, V., Kunze, M., Hillenbrand, M.: High performance cloud computing. Future Gener. Comput. Syst. 29(6), 1408–1416 (2013)CrossRefGoogle Scholar
  9. 9.
    Payne, W.: Modular HPC goes mainstream, October 2016.
  10. 10.
    Lynn, T., Xiong, H., Dong, D., Momani, B., Gravvanis, G., Filelis-Papadopoulos, C., Elster, A., Khan, M., Tzovaras, D., Giannoutakis, K., Petcu, D., Neagul, M., Drăgan, I., Kuppudayar, P., Natarajan, S., McGrath, M., Gaydadjiev, G., Becker, T., Gourinovitch, A., Kenny, D., Morrison, J.: CLOUDLIGHTNING: a framework for a self-organising and self-managing heterogeneous cloud. In: Proceedings of the 6th International Conference on Cloud Computing and Services Science. SCITEPRESS - Science and and Technology Publications (2016)Google Scholar
  11. 11.
    Geimer, M., Hoste, K., McLay, R.: Modern scientific software management using EasyBuild and Lmod. In: 2014 First International Workshop on HPC User Support Tools, pp. 41–51. HUST 2014. IEEE, Piscataway, November 2014Google Scholar
  12. 12.
    Unruh, I., Bardas, A.G., Zhuang, R., Ou, X., DeLoach, S.A.: Compiling abstract specifications into concrete systems—bringing order to the cloud. In: 28th Large Installation System Administration Conference (LISA 2014), pp. 26–42. USENIX Association, Seattle, WA (2014)Google Scholar
  13. 13.
    Morrison, J., Xiong, H., Dong, D., Momani, B.: D3.1.2 report on state of the art and draft architecture. Project deliverable, CloudLightning Project Consortium.
  14. 14.
    Marinescu, D.C., Morrison, J.P., Paya, A.: Is cloud self-organization feasible? In: Adaptive Resource Management and Scheduling for Cloud Computing Workshop, ARMS-CC 2015, pp. 119–127. Springer International Publishing (2015)Google Scholar
  15. 15.
    User’s guide for the advanced research WRF (ARW) modeling system version 3.8 (2016).

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute e-Austria TimişoaraTimişoaraRomania
  2. 2.“Victor Babeş” University of Medicine and PharmacyTimişoaraRomania
  3. 3.West University of TimişoaraTimişoaraRomania

Personalised recommendations