Distribution des Données et Rǵulation Statique des Calculs et des Communications pour la R'ólution de Grands Systèmes Lin'eŕes Creux par M'etd́e Directe

Solving large sparse symmetric positive definite systems of linear equations is a crucial and time-consuming step, arising in many scientific and engineering applications. In this work, we consider the block partitioning and scheduling problem for sparse parallel factorization without pivoting. We focus on the scalability of the parallel solver, and on the compromise between memory overhead and efficiency. We validate this study with parallel experiments on a large collection of irregular industrial problems.

Thesis