Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Grids

  • C. Banino
  • O. Beaumont
  • A. Legrand
  • Y. Robert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2367)


In this paper, we consider the problem of allocating a large number of independent, equal-sized tasks to a heterogeneous ”grid” computing platform. We use a non-oriented graph to model a grid, where resources can have different speeds of computation and communication, as well as different overlap capabilities. We show how to determine the optimal steady-state scheduling strategy for each processor.

Because spanning trees are easier to deal with in practice, a natural question arises: how to extract the best spanning tree, i.e. the one with optimal steady-state throughput, out of a general interconnection graph? We show that this problem is NP-Complete. Still, we introduce and compare several low-complexity heuristics to determine a sub-optimal spanning tree.


  1. 1.
    C. Banino, O. Beaumont, A. Legrand, and Y. Robert. Scheduling strategies for master-slave tasking on heterogeneous processor grids. Technical Report 2002-12, LIP, ENS Lyon, France, March 2002.Google Scholar
  2. 2.
    O. Beaumont, L. Carter, J. Ferrante, A. Legrand, and Y. Robert. Bandwidth-centric allocation of independent tasks on heterogeneous platforms. In International Parallel and Distributed Processing Symposium IPDPS’2002. IEEE Computer Society Press, 2002. Extended version available as LIP Research Report 2001-25.Google Scholar
  3. 3.
    O. Beaumont, A. Legrand, and Y. Robert. The master-slave paradigm with heterogeneous processors. In D.S. Katz, T. Sterling, M. Baker, L. Bergman, M. Paprzycki, and R. Buyya, editors, Cluster’2001, pages 419–426. IEEE Computer Society Press, 2001. Extended version available as LIP Research Report 2001-13.Google Scholar
  4. 4.
    O. Beaumont, A. Legrand, and Y. Robert. A polynomial-time algorithm for allocating independent tasks on heterogeneous fork-graphs. Technical Report 2002-07, LIP, ENS Lyon, France, February 2002.Google Scholar
  5. 5.
    P.B. Bhat, V.K. Prasanna, and C.S. Raghavendra. Efficient collective communication in distributed heterogeneous systems. In 19th IEEE International Conference on Distributed Computing Systems (ICDCS’99). IEEE Computer Society Press, 1999.Google Scholar
  6. 6.
    T. H. Cormen, C. E. Leiserson, and R. L. Rivest. Introduction to Algorithms. The MIT Press, 1990.Google Scholar
  7. 7.
    James Cowie, Bruce Dodson, R.-Marije Elkenbracht-Huizing, Arjen K. Lenstra, Peter L. Montgomery, and Joerg Zayer. A world wide number field sieve factoring record: on to 512 bits. In Kwangjo Kim and Tsutomu Matsumoto, editors, Advances in Cryptology-Asiacrypt’ 96, volume 1163 of LNCS, pages 382–394. Springer Verlag, 1996.CrossRefGoogle Scholar
  8. 8.
  9. 9.
    J.P Goux, S. Kulkarni, J. Linderoth, and M. Yoder. An enabling framework for master-worker applications on the computational grid. In Ninth IEEE International Symposium on High Performance Distributed Computing (HPDC’00). IEEE Computer Society Press, 2000.Google Scholar
  10. 10.
    J.-I. Hatta and S. Shibusawa. Scheduling algorithms for efficient gather operations in distributed heterogeneous systems. In 2000 International Conference on Parallel Processing (ICPP’2000). IEEE Computer Society Press, 2000.Google Scholar
  11. 11.
    E. Heymann, M.A. Senar, E. Luque, and M. Livny. Adaptive scheduling for master-worker applications on the computational grid. In R. Buyya and M. Baker, editors, Grid Computing-GRID 2000, pages 214–227. Springer-Verlag LNCS 1971, 2000.CrossRefGoogle Scholar
  12. 12.
    R. Libeskind-Hadas, J.R.K. Hartline, P. Boothe, G. Rae, and J. Swisher. On multicast algorithms for heterogeneous networks of workstations. Journal of Parallel and Distributed Computing, 61(11):1665–1679, 2001.CrossRefGoogle Scholar
  13. 13.
  14. 14.
  15. 15.
    G. Shao. Adaptive scheduling of master/worker applications on distributed computational resources. PhD thesis, Dept. of Computer Science, University Of California at San Diego, 2001.Google Scholar
  16. 16.
    J.B. Weissman. Scheduling multi-component applications in heterogeneous wide-area networks. In Heterogeneous Computing Workshop HCW’00. IEEE Computer Society Press, 2000.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • C. Banino
    • 1
  • O. Beaumont
    • 1
  • A. Legrand
    • 2
  • Y. Robert
    • 2
  1. 1.LaBRI, UMR CNRSTalence CedexFrance
  2. 2.LIP, UMR CNRS-INRIALyon Cedex 07France

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