Advancing Science at Exascale – Discover the Latest Research from NumPEx
NumPEx is leading exascale computing research, advancing high-performance computing (HPC) to tackle the biggest scientific and industrial challenges. Our team is working on the latest algorithms, architectures and software optimisations for the next generation of computational science.
Here you will find our scientific publications, hosted on HAL, with the latest results and breakthroughs from the NumPEx community. Whether you are a researcher, an industry professional or simply a curious person interested in exascale computing, these publications will give you a glimpse of the future of HPC.
We are always looking for new talents – students, researchers, engineers – who want to shape the future of computational science. Interested in contributing to this field? Have a look at our work and join us to push the limits of performance and innovation.
125 publications
Efficient Fine-Scale Simulation of Nonlinear Hyperelastic Lattice Structures
Clément Guillet, Thibaut Hirschler, Pierre Jolivet, Pablo Antolin, Robin Bouclier
Computer Methods in Applied Mechanics and Engineering · vol. 461 · pp. 119202
Mixed precision accumulation for neural network inference guided by componentwise forward error analysis
El-Mehdi El Arar, Silviu-Ioan Filip, Theo Mary, Elisa Riccietti
IMA Journal of Numerical Analysis
Two-level domain-decomposition AdaGrad method for scalable training of graph neural networks
Laurynas Varnas, Julien Herrmann, Alexander Heinlein, Serge Gratton, Alena Kopaničáková
Preprint
Réduction dynamique des traces par l’analyse de performance a la volée
Tom Gavé
Ecole Nationale Supérieure d'Electronique, Informatique et Radiocommunications de Bordeaux
Sharp Probabilistic Normwise Backward Error Bounds for LU Factorization
Liam Burke, El-Mehdi El Arar, Stef Graillat, Theo Mary
Preprint
QABBA: Symbolic Time Series Compression via Integer-Quantized Aggregation
Erin Carson, Xinye Chen, Fei He, Cheng Kang
Preprint
Longest-Path-Based Task Splitting for Homogeneous Platforms
Thomas Morin, Nathalie Furmento, Abdou Guermouche, Samuel Thibault, Pierre-André Wacrenier
PPAM 2026 - International Conference on Parallel Processing and Applied Mathematics · Poznan, PL
Mixed Precision Augmented GMRES
Yongseok Jang, Pierre Jolivet, Theo Mary
Numerical Linear Algebra with Applications · vol. 33 · no. 4 · pp. e70117
Automated Numerical Stability Analysis of Deep Learning Operators
Xinye Chen
Preprint · arxiv
A fixed-accuracy randomized interpolative decomposition based on pivoted QR
Alfredo Buttari, Karmijn Hoogveld, Theo Mary
Preprint
TOTO: Transparent I/O Tuning for HPC Applications
Francieli Boito, Luan Teylo, Mihail Popov, Laora Aimi, Alexis Bandet, Laércio Lima Pilla + 1 more
ICS 2026 - International Conference on Supercomputing · Belfast, GB
Mixed precision Newton's method for optimization
Nicolas Brisebarre, Giuseppe Carrino, Theo Mary, Elisa Riccietti
Preprint
