OpenMOLE: a Workflow Engine for Distributed Medical Image Analysis

Abstract : This 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.
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Communication dans un congrès
International Workshop on High Performance Computing for Biomedical Image Analysis (part of MICCAI 2014), Sep 2014, Boston, United States. 2014
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https://hal.inria.fr/hal-01099220
Contributeur : Jonathan Passerat-Palmbach <>
Soumis le : mercredi 7 janvier 2015 - 16:15:16
Dernière modification le : jeudi 12 avril 2018 - 01:49:30
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Distributed under a Creative Commons Paternité 4.0 International License

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  • HAL Id : hal-01099220, version 1

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Jonathan Passerat-Palmbach, Mathieu Leclaire, Romain Reuillon, Zehan Wang, Daniel Rueckert. OpenMOLE: a Workflow Engine for Distributed Medical Image Analysis. International Workshop on High Performance Computing for Biomedical Image Analysis (part of MICCAI 2014), Sep 2014, Boston, United States. 2014. 〈hal-01099220〉

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