Výsledky vyhledávání - "Antoine Petitet"

A Deep Reinforcement Learning Heuristic for SAT based on Antagonist Graph Neural Networks

Autor: Thomas Fournier, Arnaud Lallouet, Télio Cropsal, Gaël Glorian, Alexandre Papadopoulos, Antoine Petitet, Guillaume Perez, Suruthy Sekar, Wijnand Suijlen

Publikováno v: 2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6fe32f403e4834b8ce970ae9a13d4050
https://doi.org/10.1109/ictai56018.2022.00185

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A Parallel Algorithm for GAC Filtering of the Alldifferent Constraint

Autor: Wijnand Suijlen, Félix de Framond, Arnaud Lallouet, Antoine Petitet

Publikováno v: Integration of Constraint Programming, Artificial Intelligence, and Operations Research ISBN: 9783031080104

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::101ecad84b13b49cf71623f81d603c03
https://doi.org/10.1007/978-3-031-08011-1_26

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Minimizing development and maintenance costs in supporting persistently optimized BLAS

Autor: R. Clint Whaley, Antoine Petitet

Publikováno v: Software: Practice and Experience. 35:101-121

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7a94d5ab6e814819f02738e435f2ddd2
https://doi.org/10.1002/spe.626

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Efficient Solution Of The Rank-Deficient Linear Least Squares Problem

Autor: Antoine Petitet, Enrique S. Quintana-Ortí, Gregorio Quintana-Ortí

Publikováno v: SIAM Journal on Scientific Computing. 20:1155-1163

In this paper we present several new fast and reliable algorithms for solving rank-deficient linear least squares problems by means of the complete orthogonal decomposition. Experimental comparison of our algorithms with the existing implementations

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7c8c379b50f6c56d646984a956c3702a
https://doi.org/10.1137/s1064827596304836

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Scheduling Block-Cyclic Array Redistribution**This work was supported in part by the National Science Foundation Grant No. ASC-9005933; by the Defense Advanced Research Projects Agency under contract DAAH04-95-1-0077, administered by the Army Research Office; by the Department of Energy Office of Computational and Technology Research, Mathematical, Information, and Computational Sciences Division under Contract DE-AC05-84OR21400; by the National Science Foundation Science and Technology Center Cooperative Agreement No. CCR-8809615; by the CNRS-ENS Lyon-INRIA project ReMaP; and by the Eureka Project EuroTOPS. Yves Robert is on leave from Ecole Normale Supérieure de Lyon and is partly supported by DRET/DGA under contract ERE 96-1104/A000/DRET/DS/SR. Antoine Petitet now is with the NEC Research Center in Sankt Augustin, Germany. The authors acknowledge the use of the Intel Paragon XP/S 5 computer, located in the Oak Ridge National Laboratory Center for Computational Sciences, funded by the Department of Energy’s Mathematical, Information, and Computational Sciences Division subprogram of the Office of Computational and Technology Research

Autor: Frédéric Desprez, Jack Dongarra, Antoine Petitet, Cyril Randriamaro, Yves Robert

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0729ed2bd58b6a2a3771ad59fef492cd
https://doi.org/10.1016/s0927-5452(98)80028-2

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ScaLAPACK tutorial

Autor: Jack Dongarra, Antoine Petitet

Publikováno v: Lecture Notes in Computer Science ISBN: 9783540609025

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::984b2b33731e9b309ef0d9d544ba895e
https://doi.org/10.1007/3-540-60902-4_20

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