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Knowledge-Based Resource Management for Distributed Problem Solving

  • Conference paper
Knowledge Engineering and Management

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 123))

Abstract

Knowledge-based approach for composite high-performance application building and execution is proposed as a solution to solving complex computational-intensive scientific tasks using set of existing software packages. The approach is based on semantic description of existing software, used within composite application. It allows building applications according to user quality requirements and domain-specific task description. CLAVIRE platform is described as an example of successful implementation of proposed approach’s basic principles. Exploration of described software solution performance characteristics is presented.

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References

  1. Hey, T., Tansley, S., Tolle, K. (eds.): The Fourth Paradigm. Data-Intensive Scientific Discovery, Microsoft (2009)

    Google Scholar 

  2. Rice, J.R., Boisvert, R.F.: From Scientific Software Libraries to Problem-Solving Environments. IEEE Computational Science & Engineering 3(3), 44–53 (1996)

    Article  Google Scholar 

  3. Kishimoto, Y., Ichikawa, S.: Optimizing the Configuration of a Heterogeneous Cluster with Multiprocessing and Execution-Time Estimation. Parallel Computing 31(7), 691–710 (2005)

    Article  Google Scholar 

  4. Dolan, E.D., Moré, J.J.: Benchmarking Optimization Software with Performance Profiles. Mathematical Programming 91(2), 201–213 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  5. HPC-NASIS, http://hpc-nasis.ifmo.ru/

  6. Boukhanovsky, A.V., Kovalchuk, S.V., Maryin, S.V.: Intelligent Software Platform for Complex System Computer Simulation: Conception. In: Architecture and Implementation, vol. 10, pp. 5–24. Izvestiya VUZov, Priborostroenie (2009) (in Russian)

    Google Scholar 

  7. Start GridNNN, http://ngrid.ru/ngrid/

  8. Kim, J., et al.: Principles For Interactive Acquisition And Validation Of Workflows. Journal of Experimental & Theoretical Artificial Intelligence 22, 103–134 (2010)

    Article  MATH  Google Scholar 

  9. Gubała, T., Bubak, M., Malawski, M., Rycerz, K.: Semantic-based grid workflow composition. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Waśniewski, J. (eds.) PPAM 2005. LNCS, vol. 3911, pp. 651–658. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  10. Gil, Y.: From Data to Knowledge to Discoveries: Scientific Workflows and Artificial Intelligence. Scientific Programming 17(3), 1–25 (2008)

    Google Scholar 

  11. Blythe, J., et al.: Transparent Grid Computing: a Knowledge-Based Approach. In: Proceedings of the 15th Annual Conference on Innovative Applications of Artificial Intelligence, pp. 12–14 (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. e-Science Research Institute, National Research University ITMO, Saint-Petersburg, Russian Federation

    Sergey Kovalchuk, Aleksey Larchenko & Alexander Boukhanovsky

Authors
  1. Sergey Kovalchuk
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  2. Aleksey Larchenko
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  3. Alexander Boukhanovsky
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Yinglin Wang

  2. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, Sichuan Province, China

    Tianrui Li

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© 2011 Springer-Verlag Berlin Heidelberg

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Kovalchuk, S., Larchenko, A., Boukhanovsky, A. (2011). Knowledge-Based Resource Management for Distributed Problem Solving. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-25661-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25660-8

  • Online ISBN: 978-3-642-25661-5

  • eBook Packages: EngineeringEngineering (R0)

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