Scheduling strategies for mixed data and task parallelism on heterogeneous processor grids - Inria - Institut national de recherche en sciences et technologies du numérique
Rapport (Rapport De Recherche) Année : 2002

Scheduling strategies for mixed data and task parallelism on heterogeneous processor grids

Résumé

In this paper, we consider the execution of a complex application on a heterogeneous grid computing platform. The complex application consists of a suite of identical, independent problems to be solved. In turn, each problem consists of a set of tasks. There are dependences (precedence constraints) between these tasks. A typical example is the repeated execution of the same algorithm on several distinct data samples. We use a non-oriented graph to model the grid platform, where resources have different speeds of computation and communication. We show how to determine the optimal steady-state scheduling strategy for each processor (the fraction of time spent computing and the fraction of time spent communicating with each neighbor). This result holds for a quite general framework, allowing for cycles and multiple paths in the platform graph.
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Dates et versions

hal-00807405 , version 1 (03-04-2013)

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  • HAL Id : hal-00807405 , version 1

Citer

Olivier Beaumont, Arnaud Legrand, Yves Robert. Scheduling strategies for mixed data and task parallelism on heterogeneous processor grids. [Research Report] 2002-20, 2002. ⟨hal-00807405⟩
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