Hectiling: An Integration of Fine and Coarse-Grained Load-Balancing Strategies

  • Authors:
  • Samuel H. Russ;Ioana Banicescu;Sheikh Ghafoor;Bharathi Janapareddi;Jonathan Robinson;Rong Lu

  • Affiliations:
  • -;-;-;-;-;-

  • Venue:
  • HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
  • Year:
  • 1998

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Abstract

General-purpose programmers have come to expect a high degree of portability among widely varying architectures. Advances in run-time systems for parallel programs have been proposed in order to harness available resources as efficiently as possible. Simultaneously, advances in algorithmic ways of dynamically balancing computational load have been proposed in order to respond to variations in actual performance and therefore in runtime. The primary mechanism for harnessing idle resources effectively, task migration, can be used alongside the primary mechanism for dynamic load balancing, data redistribution. Besides the fact that the two methods can be used simultaneously to spur further increases in performance, the run-time information-gathering infrastructure necessary to detect and use idle resources can also benefit dynamically load-balanced applications. This paper describes an architecture for and preliminary implementation of a system that combines data-parallel load-balancing with task-parallel load-balancing. Performance test results are included as well.