A First Step Towards Automatically Building Network Representations

To fully harness Grids, users or middlewares must have some knowledge on the topology of the platform interconnection network. As such knowledge is usually not available, one must uses tools which automatically build a topological network model through some measurements. In this article, we define a methodology to assess the quality of these network model building tools, and we apply this methodology to representatives of the main classes of model builders and to two new algorithms. We show that none of the main existing techniques build models that enable to accurately predict the running time of simple application kernels for actual platforms. However some of the new algorithms we propose give excellent results in a wide range of situations

A First Step Towards Automatically Building Network Representations

To fully harness Grids, users or middlewares must have some knowledge on the topology of the platform interconnection network. As such knowledge is usually not available, one must uses tools which automatically build a topological network model through some measurements. In this article, we define a methodology to assess the quality of these network model building tools, and we apply this methodology to representatives of the main classes of model builders and to two new algorithms. We show that none of the main existing techniques build models that enable to accurately predict the running time of simple application kernels for actual platforms. However some of the new algorithms we propose give excellent results in a wide range of situations.Afin de tirer le meilleur parti des grilles, les utilisateurs et les intergiciels doivent avoir connaissance de la topologie du réseau d’interconnexion de la plate-forme utilisée. Comme cette connaissance n’est généralement pas disponible a priori, on doit avoir recours à des outils construisant un modèle du réseau d’interconnexion à partir de mesures. Dans cet article nous définissons une méthodologie pour évaluer la qualité de ces outils de construction de modèles de réseau, et nous l’appliquons à des représentants des principaux types de reconstructeurs de topologies, ainsi qu’`à deux nouveaux algorithmes. Nous montrons qu’aucune des techniques existantes ne produit des modèles qui permettent de prédire avec précision le temps d’exécution sur les plates-formes actuelles de simples noyaux d’applications. Au contraire, un des nouveaux algorithmes obtient de très bons résultats dans des situations très variées

Mapping and Load-Balancing Iterative Computations on Heterogeneous Clusters

This paper is devoted to mapping iterative algorithms onto heterogeneous clusters. The application data is partitioned over the processors, which are arranged along a virtual ring. At each iteration, independent calculations are carried out in parallel, and some communications take place between consecutive processors in the ring. The question is to determine how to slice the application data into chunks, and to assign these chunks to the processors, so that the total execution time is minimized. One major difficulty is to embed a processor ring into a network that typically is not fully connected, so that some communication links have to be shared by several processor pairs. We establish a complexity result that assesses the difficulty of this problem, and we design a practical heuristic that provides efficient mapping, routing, and data distribution schemes

Mapping and Load-Balancing Iterative Computations on Heterogeneous Clusters with Shared Links

International audienceNo abstrac

Mapping and Load-Balancing Iterative Computations on Heterogeneous Clusters with Shared Links

International audienceNo abstrac