Pierre Jolivet

dblp:136/7944 · DBLP profile ↗
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4ranked-venue papers
2as first author
1since 2021 · last 2023
0009-0000-3410-0884ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 3 · 2 first-authorTheory of computation · 1 · 1 since 2021
YearPublicationVenuePosition
2023 Improvements to SLEPc in Releases 3.14-3.18
abstract
This short article describes the main new features added to SLEPc, the Scalable Library for Eigenvalue Problem Computations, in the past two and a half years, corresponding to five release versions. The main novelty is the extension of the SVD module with new problem types, such as the generalized SVD or the hyperbolic SVD. Additionally, many improvements have been incorporated in different parts of the library, including contour integral eigensolvers, preconditioning, and GPU support.
José E. Román, Fernando Alvarruiz, Carmen Campos, Lisandro Dalcín, Pierre Jolivet, Alejandro Lamas Daviña
ACM Trans. Math. Softw.5
2019 Microwave tomographic imaging of cerebrovascular accidents by using high-performance computing
Pierre-Henri Tournier, Ioannis Aliferis, Marcella Bonazzoli, Maya de Buhan, Marion Darbas, Victorita Dolean, Frédéric Hecht, Pierre Jolivet, Ibtissam El Kanfoud, Claire Migliaccio, Frédéric Nataf, Christian Pichot, Serguei Semenov
Parallel Comput.8
2016 Block iterative methods and recycling for improved scalability of linear solvers
abstract
Contemporary large-scale Partial Differential Equation (PDE) simulations usually require the solution of large and sparse linear systems. Moreover, it is often needed to solve these linear systems with different or multiple Right-Hand Sides (RHSs). In this paper, various strategies will be presented to extend the scalability of existing multigrid or domain decomposition linear solvers using appropriate recycling strategies or block methods-i.e., by treating multiple right-hand sides simultaneously. The scalability of this work is assessed by performing simulations on up to 8,192 cores for solving linear systems arising from various physical phenomena modeled by Poisson's equation, the system of linear elasticity, or Maxwell's equation. This work is shipped as part of on open-source software, readily available and usable in any C/C++, Python, or Fortran code. In particular, some simulations are performed on top of a well-established library, PETSc, and it is shown how our approaches can be used to decrease time to solution down by 30%.
Pierre Jolivet, Pierre-Henri Tournier
SC1
2013 Scalable domain decomposition preconditioners for heterogeneous elliptic problems
abstract
Domain decomposition methods are, alongside multigrid methods, one of the dominant paradigms in contemporary large-scale partial differential equation simulation. In this paper, a lightweight implementation of a theoretically and numerically scalable preconditioner is presented in the context of overlapping methods. The performance of this work is assessed by numerical simulations executed on thousands of cores, for solving various highly heterogeneous elliptic problems in both 2D and 3D with billions of degrees of freedom. Such problems arise in computational science and engineering, in solid and fluid mechanics.
Pierre Jolivet, Frédéric Hecht, Frédéric Nataf, Christophe Prud'homme
SC1