Assessing the Impact and Limits of Steady-State Scheduling for Mixed Task and Data Parallelism on Heterogeneous Platforms

Olivier Beaumont 1, 2 Arnaud Legrand 3 Loris Marchal 3, 4 Yves Robert 5
2 SCALAPPLIX - Algorithms and high performance computing for grand challenge applications
INRIA Futurs, Université Bordeaux Segalen - Bordeaux 2, Université Sciences et Technologies - Bordeaux 1, École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), CNRS - Centre National de la Recherche Scientifique : UMR5800
3 GRAAL - Algorithms and Scheduling for Distributed Heterogeneous Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
5 REMAP - Regularity and massive parallel computing
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 task graphs onto heterogeneous systems, such as clusters and grids. We advocate the use of steady-state scheduling to solve this difficult problem. Due to space limitations, we concentrate on complexity results. We show that the problem of optimizing the steady-state throughput is NP-complete in the general case. We formulate a compact version of the problem that belongs to the NP complexity class but which does not restrict the optimality of the solution. We provide many positive results in the extended version (Beaumont et al., 2004). Indeed, we show how to determine in polynomial time the best steady-state scheduling strategy for a large class of application graphs and for an arbitrary platform graphs, using a linear programming approach.
Type de document :
Communication dans un congrès
HeteroPar\'2004: International Conference on Heterogeneous Computing, Jointly Published with ISPDC\'2004: International Symposium on Parallel and Distributed Computing, 2004, Unknown, IEEE Computer Society Press, pp.296―302, 2004, <10.1109/ISPDC.2004.12>
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https://hal.inria.fr/hal-00789444
Contributeur : Arnaud Legrand <>
Soumis le : lundi 18 février 2013 - 11:51:35
Dernière modification le : vendredi 11 septembre 2015 - 01:06:01

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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. HeteroPar\'2004: International Conference on Heterogeneous Computing, Jointly Published with ISPDC\'2004: International Symposium on Parallel and Distributed Computing, 2004, Unknown, IEEE Computer Society Press, pp.296―302, 2004, <10.1109/ISPDC.2004.12>. <hal-00789444>

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