Théo Mary

Orcid: 0000-0001-9949-4634

Affiliations:
  • University of Manchester, UK
  • Paul Sabatier University, Toulouse, France (PhD 2017)


According to our database1, Théo Mary authored at least 25 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Five-Precision GMRES-Based Iterative Refinement.
SIAM J. Matrix Anal. Appl., March, 2024

Communication Avoiding Block Low-Rank Parallel Multifrontal Triangular Solve with Many Right-Hand Sides.
SIAM J. Matrix Anal. Appl., March, 2024

Adaptive Precision Sparse Matrix-Vector Product and Its Application to Krylov Solvers.
SIAM J. Sci. Comput., February, 2024

2023
Modular Matrix Multiplication on GPU for Polynomial System Solving.
ACM Commun. Comput. Algebra, June, 2023

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement.
ACM Trans. Math. Softw., March, 2023

Mixed precision LU factorization on GPU tensor cores: reducing data movement and memory footprint.
Int. J. High Perform. Comput. Appl., March, 2023

Matrix Multiplication in Multiword Arithmetic: Error Analysis and Application to GPU Tensor Cores.
SIAM J. Sci. Comput., February, 2023

2022
Mixed precision algorithms in numerical linear algebra.
Acta Numer., May, 2022

Block low-rank single precision coarse grid solvers for extreme scale multigrid methods.
Numer. Linear Algebra Appl., 2022

2021
Stochastic Rounding and Its Probabilistic Backward Error Analysis.
SIAM J. Sci. Comput., 2021

Block Low-Rank Matrices with Shared Bases: Potential and Limitations of the BLR<sup>2</sup> Format.
SIAM J. Matrix Anal. Appl., 2021

2020
Sharper Probabilistic Backward Error Analysis for Basic Linear Algebra Kernels with Random Data.
SIAM J. Sci. Comput., 2020

A Class of Fast and Accurate Summation Algorithms.
SIAM J. Sci. Comput., 2020

Mixed Precision Block Fused Multiply-Add: Error Analysis and Application to GPU Tensor Cores.
SIAM J. Sci. Comput., 2020

2019
Performance and Scalability of the Block Low-Rank Multifrontal Factorization on Multicore Architectures.
ACM Trans. Math. Softw., 2019

A New Approach to Probabilistic Rounding Error Analysis.
SIAM J. Sci. Comput., 2019

A New Preconditioner that Exploits Low-Rank Approximations to Factorization Error.
SIAM J. Sci. Comput., 2019

Robust and Accurate Stopping Criteria for Adaptive Randomized Sampling in Matrix-Free Hierarchically Semiseparable Construction.
SIAM J. Sci. Comput., 2019

Bridging the Gap Between Flat and Hierarchical Low-Rank Matrix Formats: The Multilevel Block Low-Rank Format.
SIAM J. Sci. Comput., 2019

Improving the Complexity of Block Low-Rank Factorizations with Fast Matrix Arithmetic.
SIAM J. Matrix Anal. Appl., 2019

2018
Matrix-free construction of HSS representation using adaptive randomized sampling.
CoRR, 2018

2017
Block Low-Rank multifrontal solvers: complexity, performance, and scalability. (Solveurs multifrontaux exploitant des blocs de rang faible: complexité, performance et parallélisme).
PhD thesis, 2017

On the Complexity of the Block Low-Rank Multifrontal Factorization.
SIAM J. Sci. Comput., 2017

2015
Performance of random sampling for computing low-rank approximations of a dense matrix on GPUs.
Proceedings of the International Conference for High Performance Computing, 2015

2014
Access-averse framework for computing low-rank matrix approximations.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014


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