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Model Exploration Using OpenMOLE - a workflow engine for large scale distributed design of experiments and parameter tuning

By Romain Reuillon, Mathieu Leclaire and Jonathan Passerat-Palmbach

Abstract

International audienceOpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution.Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. In this work, we briefly expose the strong assets of OpenMOLE and demonstrate its efficiency at exploring the parameter set of an agent simulation model. We perform a multi-objective optimisation on this model using computationally expensive Genetic Algorithms (GA). OpenMOLE hides the complexity of designing such an experiment thanks to its DSL, and transparently distributes the optimisation process. The example shows how an initialisation of the GA with a population of 200,000 individuals can be evaluated in one hour on the European Grid Infrastructure

Topics: Distributed computing, Scientific workflows, Design of Experiments, Evolutionary Algorithms, Model Exploration, [ INFO.INFO-DC ] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation
Publisher: HAL CCSD
Year: 2015
OAI identifier: oai:HAL:hal-01163457v1
Provided by: Hal-Diderot

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