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Large scale in transit computation of quantiles for ensemble runs

Abstract : The classical approach for quantiles computation requires availability of the full sample before ranking it. In uncertainty quantification of numerical simulation models, this approach is not suitable at exascale as large ensembles of simulation runs would need to gather a prohibitively large amount of data. This problem is solved thanks to an on-the-fly and iterative approach based on the Robbins-Monro algorithm. This approach relies on Melissa, a file avoiding, adaptive, fault-tolerant and elastic framework. On a validation case producing 11 TB of data, which consists in 3000 fluid dynamics parallel simulations on a 6M cell mesh, it allows on-line computation of spatio-temporal maps of percentiles.
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Contributor : Bertrand Iooss Connect in order to contact the contributor
Submitted on : Friday, May 10, 2019 - 3:20:30 PM
Last modification on : Wednesday, October 26, 2022 - 8:14:07 AM


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  • HAL Id : hal-02016828, version 2
  • ARXIV : 1905.04180


Alejandro Ribes, Théophile Terraz, Bertrand Iooss, Yvan Fournier, Bruno Raffin. Large scale in transit computation of quantiles for ensemble runs. [Research Report] EDF R&D. 2019. ⟨hal-02016828v2⟩



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