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Parallel Computational Fluid Dynamics 2008 pp 339–346Cite as

Dynamic Load Balancing on Networked Multi-core Computers

  • Conference paper
  • First Online:

  • 2006 Accesses

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 74))

Abstract

As multi-core computers becoming the main computation force of the computer network, dynamic load balancing for parallel applications on multi-core computers needs to be studied. The paper describes a method for extending the dynamic load balancing tool to support multi-core computers. The method scales all cost function information into per CPU core unit and performs dynamic load balancing in terms of CPU cores. The parallel processes are assigned to each computer (not each CPU core) assuming that the operating system assigns the parallel processes equally among all CPU cores. The proposed tool has been successfully tested for supporting parallel CFD applications.

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References

  1. L. Chai, Q. Gao, Panda, K. Dhabaleswar, Understanding the Impact of Multi-Core Architecture in Cluster Computing: A Case Study with Intel Dual-Core System, Seventh IEEE International Symposium on Cluster Computing and the Grid, pp. 471-478 Electronic Edition.

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  2. The cell project at IBM research, http://www.research.ibm.com/cell

  3. Y.P. Chien, J.D. Chen, A. Ecer, H.U. Akay, and J. Zhou, DLB 2.0 – A Distributed Environment Tool for Supporting Balanced Execution of Multiple Parallel Jobs on Networked Computers, Proceedings of Parallel Computational Fluid Dynamics 2001, May 2001, Amsterdam, Holland.

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  4. S. Secer, Genetic Algorithms and Communication Cost Function for Parallel CFD Problems, M.S.E.E. Thesis, Purdue University, May 1997.

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  5. CFD test solver, http://www.engr.iupui.edu/me/newmerl/cfdl_software.htm

  6. MPICH 2, http://www-unix.mcs.anl.gov/mpi/mpich2/

  7. S. Chien, G. Makinabakan, A. Ecer, and H.U. Akay, Non-Intrusive Data Collection for Load Balancing of Parallel Applications, Proceedings of Parallel Computational Fluid Dynamics 2006, Busan, Korea, May 13-15, 2006.

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Author information

Authors and Affiliations

  1. Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis, 723 W. Michigan Street, Indianapolis, IN, 46202, USA

    Stanley Chien, Gun Makinabakan, Akin Ecer & Hasan Akay

  2. Mechanical, Aerospace and Structural Engineering Department, Washington University in St. Louis, St. Louis, 63130, MO, USA

    Stanley Chien, Gun Makinabakan, Akin Ecer & Hasan Akay

Authors
  1. Stanley Chien
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  2. Gun Makinabakan
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  3. Akin Ecer
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  4. Hasan Akay
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Corresponding author

Correspondence to Stanley Chien .

Editor information

Editors and Affiliations

  1. , Institut Camille Jordan, Université Lyon 1 - CNRS, Bd du 11 Novembre 1918 43, Villeurbanne, 69622, France

    Damien Tromeur-Dervout

  2. , Institut für Technische Mechanik, TU Clausthal, Adolph-Roemer-Str. 2A2a, Clausthal-Zellerfeld, 38678, Germany

    Gunther Brenner

  3. Daresbury Laboratory, Daresbury Science & Innovation Campus, Science & Technology Facilities Council, Warrington, WA4 4AD, Cheshire, United Kingdom

    David R. Emerson

  4. INRIA - SAGE, Campus de Beaulieu, Rennes, 35042, France

    Jocelyne Erhel

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Chien, S., Makinabakan, G., Ecer, A., Akay, H. (2010). Dynamic Load Balancing on Networked Multi-core Computers. In: Tromeur-Dervout, D., Brenner, G., Emerson, D., Erhel, J. (eds) Parallel Computational Fluid Dynamics 2008. Lecture Notes in Computational Science and Engineering, vol 74. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14438-7_36

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