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Task Allocation in Heterogeneous Computing Environment by Genetic Algorithm

  • Soumen Dey
  • Subhodip Majumder
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2571)

Abstract

This paper presents an efficient technique for mapping a set of tasks onto a set of heterogeneous processors. The tasks require data communication between them. The system is assumed to be completely heterogeneous, where the processing speeds, memory access speeds, communication latency between processors and the network topology are all considered being non-uniform. Typically, the numbers of tasks are much larger than the number of processor available. The problem of optimal mapping of the tasks to the processors such that the application run -time is minimized is NP-Complete. The searching capabilities of genetics algorithms are utilized to perform the optimal/near optimal mapping.

Keywords

Genetic Algorithm Local Memory Task Allocation Task Graph Heterogeneous Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [5]
    Heterogeneous Computing: A New Computing Paradigm by Raju D. Venkataramana Department of Computer Science & Engineering, University of South Florida, TampaGoogle Scholar
  2. [6]
    A Heuristic model for task allocation in heterogeneous distributed computing systems: by A. Abdelmageed Elsadek B. Earl Wells, Electrical and Computer Engineering The University of Alabama in Huntsville, Huntsville, AL 35899, U.S.A.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Soumen Dey
    • 1
  • Subhodip Majumder
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of CalcuttaKolkataIndia

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