Trading performance for memory in sparse direct solvers using low-rank compression

Autor: Grégoire PICHON, Thibault Marette, Loris Marchal, Frédéric Vivien

Publikováno v: Future Generation Computer Systems
Future Generation Computer Systems, 2022, 130, pp.307-320. ⟨10.1016/j.future.2021.12.018⟩
[Research Report] RR-9368, INRIA. 2020
Future Generation Computer Systems, Elsevier, In press

Sparse direct solvers using Block Low-Rank compression have been proven efficient to solve problems arising in many real-life applications. Improving those solvers is crucial for being able to 1) solve larger problems and 2) speed up computations. A

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f63db4c7540f15de729501627227b184
https://doi.org/10.1016/j.future.2021.12.018

Synergies between Numerical Methods for Kinetic Equations and Neural Networks

Autor: Schotthöfer, Steffen

The overarching theme of this work is the efficient computation of large-scale systems. Here we deal with two types of mathematical challenges, which are quite different at first glance but offer similar opportunities and challenges upon closer exami

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9615077cd1a58c7f088a5ff28602143

Algèbre linéaire numérique et analyse de données en grande dimensions utilisant le format tenseur

Autor: Iannacito, Martina

Publikováno v: Numerical Analysis [cs.NA]. Université de Bordeaux, 2022. English. ⟨NNT : 2022BORD0377⟩

This work aims to establish which theoretical properties of classical linear algebra techniques developed in two different contexts, that are numerical linear algebra and data analysis, are saved and which are lost, once they are extended to tensors

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::f893e693806ebec2683964c7c0ad72fa
https://theses.hal.science/tel-03952711/document

Amélioration de la mémoire et du temps des solveurs directs creux linéaires de rang faible

Autor: Korkmaz, Esragul

Publikováno v: Data Structures and Algorithms [cs.DS]. Université de Bordeaux, 2022. English. ⟨NNT : 2022BORD0254⟩

Through the recent improvements toward exascale supercomputer systems, huge computations can be performed in reasonable times by using massively parallelized operations. Unfortunately, the increase of the computational units in these systems does not

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::929f6fd59416fb2136c35dcc9006549d
https://theses.hal.science/tel-03875858/document

Direct solution of larger coupled sparse/dense linear systems using low-rank compression on single-node multi-core machines in an industrial context

Autor: Emmanuel Agullo, Marek Felsoci, Guillaume Sylvand

Publikováno v: [Research Report] RR-9453, Inria Bordeaux Sud-Ouest. 2022, pp.25
IPDPS 2022-36th IEEE International Parallel and Distributed Processing Symposium
IPDPS 2022-36th IEEE International Parallel and Distributed Processing Symposium, May 2022, Lyon, France. pp.11, ⟨10.1109/IPDPS53621.2022.00012⟩

International audience; While hierarchically low-rank compression methods are now commonly available in both dense and sparse direct solvers, their usage for the direct solution of coupled sparse/dense linear systems has been little investigated. The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad5f55a63f19db7f819224d8671dee4d
https://inria.hal.science/hal-03557692