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, Eric Darve, Luc Giraud, Yuval Harness. Low-rank Factorizations in Data Sparse Hierarchical Algorithms for Preconditioning Symmetric Positive Definite Matrices. [Research Report] RR-9200, Inria Bordeaux Sud-Ouest. 2018

Emmanuel Agullo, Luc Giraud, Louis Poirel. Robust coarse spaces for abstract Schwarz preconditioners via generalized eigenproblems. International conference on domain decomposition methods, DD24, Feb 2017, Svalbard, Norway

Emmanuel Agullo, Olivier Aumage, Mathieu Faverge, Nathalie Furmento, Florent Pruvost, et al.. Achieving High Performance on Supercomputers with a Sequential Task-based Programming Model. IEEE Transactions on Parallel and Distributed Systems, Institute of Electrical and Electronics Engineers, In press

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

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