On-line, non-clairvoyant optimization of workflow activity granularity on grids

Rafael Ferreira da Silva 1 Tristan Glatard 1 Frédéric Desprez 2
1 Images et Modèles
CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé
2 AVALON - Algorithms and Software Architectures for Distributed and HPC Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
Abstract : Controlling the granularity of workflow activities executed on widely distributed computing platforms such as grids is required to reduce the impact of task queuing and data transfer time. Most existing granularity control approaches assume extensive knowledge about the applications and resources (e.g. task duration on each resource), and that both the workload and available resources do not change over time. We propose a granularity control algorithm for platforms where such clairvoyant and offline conditions are not realistic. Our method groups tasks when the fineness degree of the application, which takes into account the ratio of shared data and the queuing/round-trip time ratio, becomes higher than a threshold determined from execution traces. The algorithm also de-groups task groups when new resources arrive. The application's behavior is constantly monitored so that the characteristics useful for the optimization are progressively discovered. Experimental results, obtained with 3 workflow activities deployed on the European Grid Infrastructure, show that (i) the grouping process yields speed-ups of about 2.5 when the amount of available resources is constant and that (ii) the use of de-grouping yields speed-ups of 2 when resources progressively appear.
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Rafael Ferreira da Silva, Tristan Glatard, Frédéric Desprez. On-line, non-clairvoyant optimization of workflow activity granularity on grids. 19th International Conference Euro-Par 2013, Aug 2013, Aachen, Germany. pp.255-266. ⟨hal-00849988⟩

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