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TERATEC 2017 Forum
Workshop 8 - Wednesday, June 28 from 14:00 to 17:30

Numerical precision and stability in HPC simulation

Improving performance and reliability of industrial simulations thanks to stochastic arithmetic

Abstract :  In the domain of numerical simulation, code performance and result quality are often seen as antagonist challenges. In an industrial context, priority is often given to performance to the detriment of quality. We show in this talk some industrial challenges related to the numerical quality of simulations. We describe three tools based on stochastic arithmetic that enable one to introduce numerical validation in an industrial process. The CADNA and Verrou tools use stochastic arithmetic to evaluate the numerical quality of instrustrial codes. The PROMISE software enables one to optimize the allocation of variables in a simulation while controlling the realiability of the computed results. From a required accuracy on results, PROMISE can be used to generate a mixed-precision code and thus improve the performance obtained in an SIMD environment.

Bio : After his PhD thesis (collaboration between INRIA Bordeaux Sud-Ouest and EDF R&D) about Domain Decomposition methods for Simplified Transport Equation in neutronics, Bruno Lathuilière joined EDF R&D in the group "Analysis and Numericals Modeling". He develops solvers for various applications: Micado (Neutron Transport) , Athena (US waves propagation)... From its development experience, he got interested in problems related to numerical quality for industrial applications. In 2014 he started with François Févotte the development of Verrou and since 2016 he is the manager of the Numerical Quality workpackage in the PQuaSi project (Performance and Quality of Simulations).
Bio : Fabienne Jézéquel has been Associate Professor in Computer Science in Panthéon-Assas University (Paris 2) since 1997. She is co-Leader of the PEQUAN (PErformance and QUality of Algorithms for Numerical applications) team in the Computer Science Laboratory LIP6. She received from Pierre-and-Marie Curie University (Paris 6) a PhD in 1996 and an HDR (Habilitation à Diriger des Recherches) in 2005. Her work is centered around designing efficient and reliable numerical algorithms on various architectures (computing grids, multicore processors, graphic accelerators). She is particularly interested in optimizing convergence criteria of iterative algorithms by taking into account rounding errors. She actively takes part in the development of the CADNA library that enables one to estimate the numerical quality of simulation results.

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For any other information regarding the workshops, please contact :

Jean-Pascal JEGU
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