AbstractLet A be a matrix whose sparsity pattern is a tree with maximal degree dmax. We show that if the columns of A are ordered using minimum degree on A+A∗, then factoring A using a sparse LU with partial pivoting algorithm generates only O(dmaxn) fill, requires only O(dmaxn) operations, and is much more stable than LU with partial pivoting on a general matrix. We also propose an even more efficient and just-as-stable algorithm called sibling-dominant pivoting. This algorithm is a strict partial pivoting algorithm that modifies the column preordering locally to minimize fill and work. It leads to only O(n) work and fill. More conventional column pre-ordering methods that are based (usually implicitly) on the sparsity pattern of A∗A are n...
When performing sparse matrix factorization, the ordering of matrix rows and columns has a dramatic ...
We present a family of ordering algorithms that can be used as a preprocessing step prior to perform...
AbstractWe analyze the average parallel complexity of the solution of large sparse positive definite...
We consider the problem of structure prediction for sparse LU factorization with partial pivoting. I...
International audienceThe elimination tree for unsymmetric matrices is a recent model playing import...
If A is the (sparse) coefficient matrix of linear equality constraints, for what nonsingular T is fi...
This thesis presents a parallel algorithm for the direct LU factorization of general unsymmetric spa...
Inversion of sparse matrices with standard direct solve schemes is robust but computationally expens...
In this paper we present HUND, a hypergraph-based unsymmetric nested dissection ordering algorithm f...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
AbstractConsider the problem of sparsifying a rectangular matrix with more columns than rows. This m...
Given a rectangular matrix with more columns than rows, find a base of linear combinations of the ro...
Parallel algorithms for triangularization of large, sparse, and unsymmetric matrices are presented. ...
For sparse matrices up to size $8 \times 8$, we determine optimal choices for pivot selection in Gau...
When performing sparse matrix factorization, the ordering of matrix rows and columns has a dramatic ...
We present a family of ordering algorithms that can be used as a preprocessing step prior to perform...
AbstractWe analyze the average parallel complexity of the solution of large sparse positive definite...
We consider the problem of structure prediction for sparse LU factorization with partial pivoting. I...
International audienceThe elimination tree for unsymmetric matrices is a recent model playing import...
If A is the (sparse) coefficient matrix of linear equality constraints, for what nonsingular T is fi...
This thesis presents a parallel algorithm for the direct LU factorization of general unsymmetric spa...
Inversion of sparse matrices with standard direct solve schemes is robust but computationally expens...
In this paper we present HUND, a hypergraph-based unsymmetric nested dissection ordering algorithm f...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
AbstractConsider the problem of sparsifying a rectangular matrix with more columns than rows. This m...
Given a rectangular matrix with more columns than rows, find a base of linear combinations of the ro...
Parallel algorithms for triangularization of large, sparse, and unsymmetric matrices are presented. ...
For sparse matrices up to size $8 \times 8$, we determine optimal choices for pivot selection in Gau...
When performing sparse matrix factorization, the ordering of matrix rows and columns has a dramatic ...
We present a family of ordering algorithms that can be used as a preprocessing step prior to perform...
AbstractWe analyze the average parallel complexity of the solution of large sparse positive definite...