Centralized Versus Distributed Schedulers Multiple Bag-of-Task Applications
BEAUMONT, Olivier
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
CARTER, Larry
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
FERRANTE, Jeanne
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
Voir plus >
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
BEAUMONT, Olivier
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
CARTER, Larry
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
FERRANTE, Jeanne
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
Department of Computer Science and Engineering [Univ California San Diego] [CSE - UC San Diego]
MARCHAL, Loris
Laboratoire de l'Informatique du Parallélisme [LIP]
Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL]
Laboratoire de l'Informatique du Parallélisme [LIP]
Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL]
ROBERT, Yves
Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL]
Laboratoire de l'Informatique du Parallélisme [LIP]
< Réduire
Algorithms and Scheduling for Distributed Heterogeneous Platforms [GRAAL]
Laboratoire de l'Informatique du Parallélisme [LIP]
Langue
en
Communication dans un congrès
Ce document a été publié dans
International Parallel and Distributed Processing Symposium IPDPS'2006, 2006, Rhodes Island. 2006
IEEE Computer Society Press
Résumé en anglais
Multiple applications that execute concurrently on heterogeneous platforms compete for CPU and network resources. In this paper we consider the problem of scheduling applications to ensure fair and efficient execution on ...Lire la suite >
Multiple applications that execute concurrently on heterogeneous platforms compete for CPU and network resources. In this paper we consider the problem of scheduling applications to ensure fair and efficient execution on master-worker platforms where the communication is restricted to a tree embedded in the network. The goal of the scheduling is to obtain the best throughput while enforcing some fairness between applications. We show how to derive an asymptotically optimal periodic schedule by solving a linear program expressing all problem constraints. For single-level trees, the optimal solution can be analytically computed. For large-scale platforms, gathering the global knowledge needed by the linear programming approach might be unrealistic. One solution is to adapt the multi-commodity flow algorithm of Awerbuch and Leighton, but it still requires some global knowledge. Thus, we also investigates heuristic solutions using only local information, and test them via simulations. The best of our heuristics achieves the optimal performance on about two-thirds of our test cases, but is far worse in a few cases.< Réduire
Mots clés en anglais
Parallel computing
resource sharing
scheduling
divisible load
multiple applications
resource sharing.
Project ANR
ALgorithmique des Plates-formes A Grande Echelle - ANR-05-MMSA-0006
Origine
Importé de halUnités de recherche