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Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms

Olivier Beaumont 1, 2 Arnaud Legrand 1, 2 Loris Marchal 1, 2 Yves Robert 1, 2 
1 GRAAL - Algorithms and Scheduling for Distributed Heterogeneous Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
Abstract : In this paper, we consider steady-state scheduling techniques for mapping a collection of application graphs onto heterogeneous systems, such as clusters and grids. We advocate the use of steady-state scheduling to solve this difficult problem. While the most difficult instances are shown to be NP-complete, most situations of practical interest are amenable to a periodic solution which can be described in compact form (polynomial size) and is asymptotically optimal.
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Submitted on : Friday, May 19, 2006 - 9:39:52 PM
Last modification on : Wednesday, October 26, 2022 - 8:14:04 AM

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Olivier Beaumont, Arnaud Legrand, Loris Marchal, Yves Robert. Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms. [Research Report] RR-5198, LIP RR-2004-20, INRIA, LIP. 2004, pp.44. ⟨inria-00070794⟩

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