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Scientific Computing on the Cloud (SciCloud)

last modified Feb 28, 2012 05:29 PM


The main goal of the project is to study the scope of establishing private clouds at universities. With these clouds, students and researchers can efficiently use the already existing resources of university computer networks, in solving computationally intensive scientific, mathematical, and academic problems. Traditionally such computationally intensive problems were targeted by batch-oriented models of the Grid computing domain, where as current project tries to achieve this with the more interactive and service oriented models of cloud computing that fits a larger class of applications. The established interoperable private clouds also provide better platforms for collaboration among interesting groups of universities and in testing internal pilots, innovations and social networks. The project mainly targets the development of a framework, including models and methods for establishment, proper selection, state management (managing running state and data) and interoperability of the private clouds. Once such clouds are feasible, the networks can also be leased to commercial enterprises or governmental institutions for such diverse applications as drug discovery, seismic analysis, and back-office data processing in support of e-commerce and Web services.


The Scientific Computing Cloud (SciCloud) is established at katel42 cluster at university of Tartu ( For using SciCloud resources please refer to SciCloud wiki.

If you want to get yourself familiar with SciCloud, do the following exercise.


SciCloud & Hadoop

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. To establish the Hadoop setup on the SciCloud, please go through this manual.

Open Positions


Former Staff

  • Tonis Ojandu
  • Toomas Romer




  • S. N. Srirama, P. Jakovits, E. Vainikko: Adapting Scientific Computing Problems to Clouds using MapReduce, Future Generation Computer Systems Journal, 28(1):184-192, 2012. Elsevier press. DOI 10.1016/j.future.2011.05.025
  • P. Jakovits, I. Kromonov, S. N. Srirama: Monte Carlo linear system solver using MapReduce, 4th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2011), December 5-7, 2011, pp.293-299. IEEE.
  • P. Jakovits, S. N. Srirama, E. Vainikko: MapReduce for Scientific Computing, The 14th International Parallel Computing conference (ParCo 2011), August 30-September 2, 2011. IOS Press. (In print)
  • S. N. Srirama: MWSMF: A Mediation Framework for Mobile Hosts and Enterprise on Cloud, International Journal of Pervasive Computing and Communications, ISSN: 1742-7371, 7(4):316-338, 2011. Emerald Group Publishing Limited.
  • S. N. Srirama, O. Batrashev, P. Jakovits, E. Vainikko: Scalability of Parallel Scientific Applications on the Cloud, Scientific Programming Journal, Special Issue on Science-driven Cloud Computing, 19(2-3):91-105, 2011. IOS Press. DOI 10.3233/SPR-2011-0320.
  • S. N. Srirama, V. Shor, E. Vainikko, M. Jarke: Supporting Mobile Web Service Provisioning with Cloud Computing, International Journal On Advances in Internet Technology, issn 1942-2652, 3(3&4): 261-273, 2010.
  • S. N. Srirama, P. Jakovits, E. Vainikko: Adapting Scientific Computing Problems to Clouds using MapReduce, International Conference on Utility and Cloud Computing (UCC 2010) in conjunction with the International Conference on Advanced Computing (ICoAC 2010), December 14-16, 2010.
  • S. N. Srirama, E. Vainikko, M. Jarke: Scaling Mobile Enterprise Through Cloud Computing, 7th ACM International Conference on Pervasive Services (ICPS 2010), July 13-16, 2010, pp. 69-72. ACM Press.
  • S. N. Srirama, O. Batrashev, E. Vainikko: SciCloud: Scientific Computing on the Cloud, 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2010), May 17-20, 2010, pp. 579. IEEE Computer Society.
  • S. N. Srirama, E. Vainikko, V. Shor, M. Jarke: Scalable Mobile Web Services Mediation Framework, 5th International Conference on Internet and Web Applications and Services (ICIW 2010), May 9-15, 2010, pp. 315-320. IEEE Computer Society. (Won Best Paper Award)




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