Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Gratien Jean-Marc"'
Autor:
Nastorg, Matthieu, Gratien, Jean-Marc, Faney, Thibault, Bucci, Michele Alessandro, Charpiat, Guillaume, Schoenauer, Marc
Large-scale numerical simulations often come at the expense of daunting computations. High-Performance Computing has enhanced the process, but adapting legacy codes to leverage parallel GPU computations remains challenging. Meanwhile, Machine Learnin
Externí odkaz:
http://arxiv.org/abs/2402.08296
Publikováno v:
Oil & Gas Science and Technology, Vol 69, Iss 4, Pp 753-766 (2014)
In the past few years, High Performance Computing (HPC) technologies led to General Purpose Processing on Graphics Processing Units (GPGPU) and many-core architectures. These emerging technologies offer massive processing units and are interesting fo
Externí odkaz:
https://doaj.org/article/5e8fec1ba55d4b3ba17784a0bc5a52af
Autor:
Nastorg, Matthieu, Bucci, Michele Alessandro, Faney, Thibault, Gratien, Jean-Marc, Charpiat, Guillaume, Schoenauer, Marc
This paper presents $\Psi$-GNN, a novel Graph Neural Network (GNN) approach for solving the ubiquitous Poisson PDE problems with mixed boundary conditions. By leveraging the Implicit Layer Theory, $\Psi$-GNN models an "infinitely" deep network, thus
Externí odkaz:
http://arxiv.org/abs/2302.10891
Autor:
Nastorg, Matthieu, Schoenauer, Marc, Charpiat, Guillaume, Faney, Thibault, Gratien, Jean-Marc, Bucci, Michele-Alessandro
Publikováno v:
Machine Learning and the Physical Sciences workshop, NeurIPS 2022, Dec 2022, New-Orleans, United States
This paper proposes a novel Machine Learning-based approach to solve a Poisson problem with mixed boundary conditions. Leveraging Graph Neural Networks, we develop a model able to process unstructured grids with the advantage of enforcing boundary co
Externí odkaz:
http://arxiv.org/abs/2211.11763
Autor:
Gratien Jean-Marc
Publikováno v:
Oil & Gas Science and Technology, Vol 72, Iss 2, p 12 (2017)
Nowadays, some frameworks like Arcane and Dune offer a number of advanced tools to deal with the complexity related to parallelism, meshes and linear solvers. However, they do not handle the high level complexity related to discretization methods and
Externí odkaz:
https://doaj.org/article/53496564502845dda49099a74b04c8d4
Autor:
Nakano, Tamon, Bucci, Alessandro Michele, Gratien, Jean-Marc, Faney, Thibault, Charpiat, Guillaume
The volume of fluid (VoF) method is widely used in multi-phase flow simulations to track and locate the interface between two immiscible fluids. A major bottleneck of the VoF method is the interface reconstruction step due to its high computational c
Externí odkaz:
http://arxiv.org/abs/2207.05684
Autor:
Nastorg, Matthieu a, b, ⁎, Bucci, Michele-Alessandro a, c, Faney, Thibault b, Gratien, Jean-Marc b, Charpiat, Guillaume a, Schoenauer, Marc a
Publikováno v:
In Computers and Mathematics with Applications 15 December 2024 176:270-288
Publikováno v:
Oil & Gas Science and Technology, Vol 71, Iss 6, p 65 (2016)
Solving large sparse linear systems is a time-consuming step in basin modeling or reservoir simulation. The choice of a robust preconditioner strongly impact the performance of the overall simulation. Heterogeneous architectures based on General Purp
Externí odkaz:
https://doaj.org/article/23fac2c7a0a94c748b6473343d8bed20
Publikováno v:
Oil & Gas Science and Technology, Vol 71, Iss 5, p 59 (2016)
In this work, we show how the a posteriori error estimation techniques proposed in [Di Pietro et al. (2014) Computers & Mathematics with Applications 68, 2331-2347] can be efficiently employed to improve the performance of a compositional reservoir s
Externí odkaz:
https://doaj.org/article/b9085164a9374bc4bb7cf52d245e2035
Autor:
Gratien, Jean-Marc
Publikováno v:
In Journal of Computational and Applied Mathematics 1 August 2020 373