Dynamic self-scheduling for parallel applications with task dependencies

  • Authors:
  • Aline P. Nascimento;Cristina Boeres;Vinod E. F. Rebello

  • Affiliations:
  • Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil;Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil;Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil

  • Venue:
  • Proceedings of the 6th international workshop on Middleware for grid computing
  • Year:
  • 2008

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Abstract

As grids are in essence heterogeneous, dynamic, shared and distributed environments, managing these kinds of platforms efficiently is extremely complex. Few transparent grid management systems have been developed to cope with these characteristics simultaneously and therefore both new and existing applications must be modified to execute efficiently. A promising scalable approach to deal with these intricacies is the design of self-managing or autonomic applications. Autonomic applications adapt their execution accordingly by considering knowledge about their own behaviour and environmental conditions. This paper focuses on the dynamic scheduling that provides the self-optimizing ability in autonomic applications. Being distributed, collaborative and pro-active, the proposed hierarchical scheduling infrastructure addresses important issues to enable an efficient execution in a computational grid. Unlike other approaches, the cooperative, hybrid and application-specific strategy deals effectively with task dependencies. Several experiments have been analyzed in real grid environments highlighting the efficiency and scalability of the proposed infrastructure. This paper presents an intra-site dynamic scheduling heuristic for tightly coupled parallel applications represented by DAGs.