STANISIC, Luka; THIBAULT, Samuel; LEGRAND, Arnaud; VIDEAU, Brice; MÉHAUT, Jean-François

doi:10.1007/978-3-319-09873-9_5

Métadonnées

Licence d’utilisation du document

STANISIC, Luka
Middleware efficiently scalable [MESCAL]
Laboratoire d'Informatique de Grenoble [LIG]

THIBAULT, Samuel
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]

LEGRAND, Arnaud
Middleware efficiently scalable [MESCAL]
Laboratoire d'Informatique de Grenoble [LIG]

Langue

Communication dans un congrès

Ce document a été publié dans

Euro-par - 20th International Conference on Parallel Processing, 2014-08-26, Porto. 2014-08-27p. 50-62

Springer International Publishing Switzerland

Résumé en anglais

Multi-core architectures comprising several GPUs have become mainstream in the field of High-Performance Computing. However, obtaining the maximum performance of such heterogeneous machines is challenging as it requires to carefully offload computations and manage data movements between the different processing units. The most promising and successful approaches so far rely on task-based runtimes that abstract the machine and rely on opportunistic scheduling algorithms. As a consequence, the problem gets shifted to choosing the task granularity, task graph structure, and optimizing the scheduling strategies. Trying different combinations of these different alternatives is also itself a challenge. Indeed, getting accurate measurements requires reserving the target system for the whole duration of experiments. Furthermore, observations are limited to the few available systems at hand and may be difficult to generalize. In this article, we show how we crafted a coarse-grain hybrid simulation/emulation of StarPU, a dynamic runtime for hybrid architectures, over SimGrid, a versatile simulator for distributed systems. This approach allows to obtain performance predictions accurate within a few percents on classical dense linear algebra kernels in a matter of seconds, which allows both runtime and application designers to quickly decide which optimization to enable or whether it is worth investing in higher-end GPUs or not.< Réduire

Mots clés en anglais

starpu-simgrid

URI

https://oskar-bordeaux.fr/handle/20.500.12278/198982

DOI

http://dx.doi.org/10.1007/978-3-319-09873-9_5

Project ANR

Simulation de systèmes de prochaine génération - ANR-11-INFR-0013
Solveurs pour architectures hétérogènes utilisant des supports d'exécution - ANR-13-MONU-0007

Origine

Importé de hal

Unités de recherche

Laboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800