Emmanuel AGULLO
Emmanuel Agullo Chargé de Recherches (INRIA)

Équipe LaBRI : Supports et Algorithmes pour les Applications Numériques hAutes performanceS
Fonction administrative : Correspondant de la commission "Appels à projets"
Courrier électronique : emmanuel.agulloarobaselabri.fr
Bureau : INRIA
Tél : +33 (0)5 40 00


Extrait de publications


Siegfried Cools, Emrullah Fatih Yetkin, Emmanuel Agullo, Luc Giraud, Wim Vanroose. Analyzing the Effect of Local Rounding Error Propagation on the Maximal Attainable Accuracy of the Pipelined Conjugate Gradient Method. SIAM Journal on Matrix Analysis and Applications, Society for Industrial and Applied Mathematics, 2018, 39 (1), pp.426 - 450

Emmanuel Agullo, Alfredo Buttari, Mikko Byckling, Abdou Guermouche, Ian Masliah. Achieving high-performance with a sparse direct solver on Intel KNL. [Research Report] RR-9035, Inria Bordeaux Sud-Ouest; CNRS-IRIT; Intel corporation; Université Bordeaux. 2017, pp.15

Emmanuel Agullo, Bérenger Bramas, Olivier Coulaud, Martin Khannouz, Luka Stanisic. Task-based fast multipole method for clusters of multicore processors. [Research Report] RR-8970, Inria Bordeaux Sud-Ouest. 2017, pp.15

Emmanuel Agullo, Bérenger Bramas, Olivier Coulaud, Luka Stanisic, Samuel Thibault. Modeling Irregular Kernels of Task-based codes: Illustration with the Fast Multipole Method. [Research Report] RR-9036, INRIA Bordeaux. 2017, pp.35

Emmanuel Agullo, Siegfried Cools, Luc Giraud, Wim Vanroose, Emrullah Fatih Yetkin. Soft Error in Classical PCG and its Variants: Sensitivity, Numerical Detections and Possible Recovery Policies. SIAM Annual meeting 2017, AN'17, Jul 2017, Pittsburgh, United States


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