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Journal Articles Parallel Processing Letters Year : 2003

Scheduling Strategies for Mixed Data and Task Parallelism on Heterogeneous Clusters

Abstract

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 and these dependences are organized as a tree. 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.

Dates and versions

hal-00789432 , version 1 (18-02-2013)

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Olivier Beaumont, Arnaud Legrand, Loris Marchal, Yves Robert. Scheduling Strategies for Mixed Data and Task Parallelism on Heterogeneous Clusters. Parallel Processing Letters, 2003, 13, pp.225―244. ⟨10.1142/S0129626403001252⟩. ⟨hal-00789432⟩
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