Scheduling Strategies for Mixed Data and Task Parallelism on Heterogeneous Clusters
| hal.structure.identifier | Algorithms and high performance computing for grand challenge applications [SCALAPPLIX] | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| dc.contributor.author | BEAUMONT, Olivier | |
| hal.structure.identifier | Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL] | |
| dc.contributor.author | LEGRAND, Arnaud | |
| hal.structure.identifier | Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL] | |
| hal.structure.identifier | Laboratoire de l'Informatique du Parallélisme [LIP] | |
| dc.contributor.author | MARCHAL, Loris | |
| hal.structure.identifier | Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL] | |
| dc.contributor.author | ROBERT, Yves | |
| dc.date.accessioned | 2024-04-15T09:43:56Z | |
| dc.date.available | 2024-04-15T09:43:56Z | |
| dc.date.issued | 2003 | |
| dc.identifier.issn | 0129-6264 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/197803 | |
| dc.description.abstractEn | 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. | |
| dc.language.iso | en | |
| dc.publisher | World Scientific Publishing | |
| dc.title.en | Scheduling Strategies for Mixed Data and Task Parallelism on Heterogeneous Clusters | |
| dc.type | Article de revue | |
| dc.identifier.doi | 10.1142/S0129626403001252 | |
| dc.subject.hal | Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC] | |
| bordeaux.journal | Parallel Processing Letters | |
| bordeaux.page | 225―244 | |
| bordeaux.volume | 13 | |
| bordeaux.hal.laboratories | Laboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-00789432 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-00789432v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Parallel%20Processing%20Letters&rft.date=2003&rft.volume=13&rft.spage=225%E2%80%95244&rft.epage=225%E2%80%95244&rft.eissn=0129-6264&rft.issn=0129-6264&rft.au=BEAUMONT,%20Olivier&LEGRAND,%20Arnaud&MARCHAL,%20Loris&ROBERT,%20Yves&rft.genre=article |
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