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Models for Parallel and Distributed Computation pp 53–84Cite as

Solving the Static Task Scheduling Problem for Real Machines

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Part of the book series: Applied Optimization ((APOP,volume 67))

Abstract

While the task scheduling problem under the delay model has been studied extensively, relatively little research exists for more realistic communication models such as the LogP model. The task scheduling problem is known to be NPcomplete even under the delay model (a simplified instance of the LogP model). This chapter describes the LogP model and the influence of its communication parameters on task scheduling. The similarities and differences between clustering algorithms under the delay and LogP models are discussed and a design methodology for clustering-based scheduling algorithms for the LogP model is presented. Using this design methodology, a task scheduling algorithm for the allocation of arbitrary task graphs to fully connected networks of processors under LogP model is proposed. The strategy exploits the replication and clustering of tasks to minimize the ill effects of communication on the makespan.

The authors are partially supported by research grants from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil.

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Authors and Affiliations

  1. Instituto de Computação, UFF, Rua Passo da Pátria 156, São Domingos, Niterói, 24210-240, RJ, Brazil

    Cristina Boeres & Vinod E. F. Rebello

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  1. Cristina Boeres
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  2. Vinod E. F. Rebello
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Editors and Affiliations

  1. Universidade Federal do Ceará, Brazil

    Ricardo Corrêa , Mario Fiallos  & Fernando Gomes ,  & 

  2. Universidade Federal do Rio de Janeiro, Brazil

    Inês Dutra

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Boeres, C., Rebello, V.E.F. (2002). Solving the Static Task Scheduling Problem for Real Machines. In: Corrêa, R., Dutra, I., Fiallos, M., Gomes, F. (eds) Models for Parallel and Distributed Computation. Applied Optimization, vol 67. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3609-0_3

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  • DOI: https://doi.org/10.1007/978-1-4757-3609-0_3

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