We propose a new algorithm for the fast solution of large, sparse, symmetric positive-definite
linear systems, spaND (sparsified Nested Dissection). It is based on nested dissection …

In this work, we develop a fast hierarchical solver for solving large, sparse least squares
problems. We build upon the algorithm, spaQR (sparsified QR Gnanasekaran and Darve in …

In this work, we develop a new fast algorithm, spaQR---sparsified QR---for solving large,
sparse linear systems. The key to our approach lies in using low-rank approximations to …

Solving sparse linear systems is a problem that arises in many scientific applications, and
sparse direct solvers are a time consuming and key kernel for those applications and for …

Sparse linear systems and least-squares problems appear in various scientific applications
ranging from classic domains like computational physics to growing fields like data science …

This paper adresses static resource allocation problems for irregular distributed parallel
applications. More precisely, we focus on two classical tiled linear algebra kernels: the …

De nos jours, les applications d'algèbre linéraire sont couramment utilisées pour traiter des
problèmes dont la grande taille requiert une exécution parallèle distribuée par des plate …

Linear solvers are a key component of scientific computing. In Chapter 2 we develop a new
algorithm for the fast solution of large, sparse linear systems, spaND (sparsified Nested …

MULTISCALE ALGORITHMS FOR STRUCTURED MATRICES: FAST SOLVERS AND
DEEP LEARNING A DISSERTATION SUBMITTED TO THE INSTITUTE FOR COMP Page 1 …

Solving sparse linear systems is a problem that arises in many scientific applications, and
sparse direct solvers are a time consuming and key kernel for those applications and for …