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

OpenMOLE 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.Comment: IEEE High Performance Computing and Simulation conference 2015, Jun 2015, Amsterdam, Netherland

Utilisation de EGI par la communauté des modélisateurs en systèmes complexes

International audienceUtilisation de EGI par la communauté des modélisateurs en systèmes complexe

OpenMOLE, a workflow engine specifically tailored for the distributed exploration of simulation models

International audienceComplex-systems describe multiple levels of collective structure and organization. In such systems, the emergence of global behaviour from local interactions is generally studied through large scale experiments on numerical models. This analysis generates important computation loads which require the use of multi-core servers, clusters or grid computing. Dealing with such large scale executions is especially challenging for modellers who don't possess the theoretical and methodological skills required to take advantage of high performance computing environments. That's why we have designed a cloud approach for model experimentation. This approach has been implemented in OpenMOLE (Open MOdel Experiment) as a Domain Specific Language (DSL) that leverages the naturally parallel aspect of model experiments. The OpenMOLE DSL has been designed to explore user-supplied models. It delegates transparently their numerous executions to remote execution environment. From a user perspective, those environments are viewed as services providing computing power, therefore no technical detail is ever exposed. This paper presents the OpenMOLE DSL through the example of a toy model exploration and through the automated calibration of a real-world complex system model in the field of geography

OpenMOLE: a Workflow Engine for Distributed Medical Image Analysis

International audienceThis works demonstrates how the OpenMOLE platform can provide a straightforward way to distribute heavy workloads generated by medical imaging analysis. OpenMOLE allows its users to benefit from a large set of distributed computing infrastructures such as clusters or com-puting grids, no matter the kind of application they are running. Here we extend the OpenMOLE tools to two new cluster job schedulers: SLURM and Condor. We also contribute to the Yapa pack-aging tool to support the widely spread virtual environment package from the Python programming language. Our test case shows how our developments allow a medical imaging application to be distributed using the OpenMOLE toolkit

Algorithmes évolutionnaires sur grille de calcul pour le calibrage de modéles géographiques

Sciences complexes n'est pas très heureux comme nom. Il serait mieux d'appeler cette discipline, science du complexe ou encore mieux systèmes complexes.As dynamic geographic models integrate very large number of spatial interactions, large amount of computing is necessaryfor their simulation and calibration, in order to validate them. Here a new automated calibration procedure is experimented onthe European computational grid EGI using evolutionnary algorithms. The application to the Simpoplocal model enables toreduce the computing time (one week) for managing about 7 millions runs for a preliminary validating step of the processesand parameters introduced in the model

Declarative task delegation in OpenMOLE

International audienceIn this paper we present OpenMOLE, a scientific framework providing a virtualized runtime environment for distributed computing. Current distributed execution systems do not hide the hardware and software heterogeneity of computing and data resources whereas OpenMOLE provides generic services to develop distributed scientific algorithms independently from the execution environment architecture. OpenMOLE uses abstraction layers to delegate computing tasks with the same high level interface for the major underlying architectures: local processors, batch systems, computational grids, Internet computing and cloud computing. The file access abstraction layer is another key feature helping a generic usage of the computation power provided by grids and clusters. The OpenMOLE framework has been tested with the exploration of a bacterial biofilm simulation with an individual-based model

Apports des méthodes d'exploration et de distribution appliquées à la simulation des droits à bâtir

International audienceCet article présente l'utilisation de méthodes de distribution des calculs de simulation et d'exploration de modèles de simulation de la plateforme OpenMOLE appliquées à un modèle de simulation de droits à bâtir: SimPLU3D. Cet outil simule la construction et le placement de formes bâties à l'échelle de la parcelle en respectant les règles contenues dans un Plan Local d'Urbanisme. La plateforme d'exploration de modèles OpenMOLE a été mobilisée pour deux expérimentations : la distribution du calcul des formes bâties par îlot morphologique à l'échelle de tout un département, et l'exploration de la diversité des formes bâties qu'autorise un PLU pour un îlot urbain d'une vingtaine de parcelles, au moyen de la méthode PSE (Pattern Space Exploration). La mobilisation d'infrastructures de calcul distribué et la parallélisation du calcul coordonnée par OpenMOLE a permis d'obtenir ces résultats en un temps raisonnable. Les premiers résultats présentés sont encourageants et ouvrent des perspectives d'expérimentation opérationnelle à destination d'utilisateurs (aménageurs, élus, etc.)

Urban Dynamics and Simulation Models

International audienc

Fostering the use of methods for geosimulation models sensitivity analysis and validation

International audienceIn recent years, there has been a significant increase in the development of methods to explore, validate, calibrate and optimize geosimulation models. These methods and tools remain, however, underused by simulation communities, despite an ever improved and easier access to high performance computation facilities. The OpenMOLE model exploration software (Reuillon et al., 2013) is one of the reliable approaches fully dedicated to promote these techniques. This presentation offers some feedback on the recent initiative of a researcher school in model validation, focused around models and practices linked to the OpenMOLE platform. We present the iterative exploration and validation protocol developed during the school, with methods of increasing refinement deployed on a toy geosimulation model (spatialized prey-predator agent-based model of a zombie infection, with multi-modeling paradigms to include diverse processes for agent behavior). First, we illustrate classical sensitivity analysis methods (stochasticity, design of experiments, global sensitivity indices), and then specific methods to study spatial configuration sensitivity, evolutionary computation methods for calibration and diversity search, and Bayesian calibration methods. They are applied on diverse specific submodels, highlighting specific mechanisms of the model, in order to answer associated thematic questions. We also illustrate the comparison with competing model ontologies by calibrating an ODE-based model on data generated by the simulation model. We finally synthesize lessons learned in the final challenge part of the school, consisting of the autonomous exploration of a new model instance by participants, including defining a thematic question and applying appropriate validation methods. This experiment both introduces a broad overview of new geosimulation model methods, and suggests ways to disseminate these into the modeling communities through similar pedagogical implementations