Theo Mary
CNRS researcher @ LIP6
Paris, France
theo <dot> mary <at> lip6 <dot> fr
Research interests
My research concerns the design, development, and analysis of
high
performance parallel numerical algorithms.
My recent work has particularly focused on
accelerating linear algebra computations
by harnessing
numerical approximations,
such as
low-rank compression,
mixed precision algorithms, and
randomization.
Publications
Please refer to my
publications
and
talks
pages for a list of my recent research activities.
You can also check out my
Google Scholar profile.
Open positions
We have multiple open positions at all levels (Master, PhD, postdoc, and
permanent positions) available in our team.
Please contact me if you are interested.
See also
here
for currently available Master internships.
Teaching
2024/2025 Lectures
For lectures from previous years, please contact me.
Projects
Current projects
Past projects
Supervision
Postdocs
- Yongseok Jang
(2024–ongoing, with P. Jolivet):
Krylov solvers with mixed precision and deflation.
- Antoine Jego
(2024–ongoing, with P. Amestoy, J.-Y. L'Excellent, G. Pichon):
mixed precision memory accessors for sparse direct solvers.
PhD students
- Karmijn Hoogveld
(2024–ongoing, with A. Buttari): mixed precision randomized low-rank approximations.
- Tom Caruso
(2024–ongoing, with P. Jolivet, F. Nataf, P.-H. Tournier): mixed precision domain decomposition preconditioners.
- Hugo Dorfsman
(2023–ongoing, with A. Anciaux, T. Guignon, F. Jézéquel): mixed precision BiCGstab solvers.
- Dimitri Lesnoff
(2022–ongoing, with J. Berthomieu and S. Graillat):
modular computing on GPUs for polynomial systems.
- Matthieu Robeyns
(2021–ongoing, with M. Baboulin and O. Kaya):
mixed precision low-rank matrix and tensor computing.
- Sébastien Dubois
(2022–2024, uncompleted, with L. Grigori, C. Content, E. Martin):
block low-rank domain decomposition preconditioners for CFD.
- Matthieu Gerest
(2020–2023, with F. Jézéquel, O. Boiteau, and Mumps Tech):
mixed precision block low-rank sparse direct solvers.
- Bastien Vieublé
(2019–2022, with A. Buttari):
mixed precision iterative refinement for sparse linear systems.
Master students
- Nicolas Catoni
(2024, with E. Agullo, L. Giraud, F. Jézéquel, P. Jolivet):
adaptive precision Krylov solvers.
- Roméo Molina
(2021); then PhD (2021–2024) with F. Jézéquel:
adaptive precision sparse matrix–vector product.
- Atef Dorai (2021, with F. Lopez): iterative refinement on GPU tensor cores.
Awards