Add to ORKG[Abstract] We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by means of Givens rotations. Nonzero elements of the matrix M to be decomposed are stored in a one dimensional doubly linked list data struct1tre. We will discuss a strategy to reduce fill-in in order to gain memory savings and decrease the computation times. As an application of QR factorization, we will describe the least squares problem. This algorithm has been designed for a message passing multiprocessor and we have evaluated it on the Cray T3D supercomputer using the Harwell-Boeing sparse matrix collection
The increasing complexity of modern computer architectures has greatly influenced algorithm design. ...
International audienceSolving linear equations of type Ax=b for large sparse systems frequently emer...
Abstract A Greedy Givens algorithm for computing the rank-1 updating of the QR decomposition is prop...
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by ...
. We present a parallel algorithm for the QR decomposition with column pivoting of a sparse matrix b...
AbstractThis paper discusses an extension of the pipelined Givens method for computing the QR factor...
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each ...
Abstra t. We present algorithms to determine the number of nonzeros in ea h row and olumn of the fa...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
This is a post-peer-review, pre-copyedit version of an article published in Proceedings of 4th Eurom...
Least squares problems occur in many branches of science. Typically there may be a large number of d...
Parallel algorithms for triangularization of large, sparse, and unsymmetric matrices are presented. ...
Texte intégral accessible uniquement aux membres de l'Université de LorraineThis dissertation treats...
A fundamental problem when adding column pivoting to the Householder QR fac- torization is that onl...
We introduce a parallel algorithm for computing the low rank approximation $A_k$ of a large matrix $...
The increasing complexity of modern computer architectures has greatly influenced algorithm design. ...
International audienceSolving linear equations of type Ax=b for large sparse systems frequently emer...
Abstract A Greedy Givens algorithm for computing the rank-1 updating of the QR decomposition is prop...
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by ...
. We present a parallel algorithm for the QR decomposition with column pivoting of a sparse matrix b...
AbstractThis paper discusses an extension of the pipelined Givens method for computing the QR factor...
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each ...
Abstra t. We present algorithms to determine the number of nonzeros in ea h row and olumn of the fa...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
This is a post-peer-review, pre-copyedit version of an article published in Proceedings of 4th Eurom...
Least squares problems occur in many branches of science. Typically there may be a large number of d...
Parallel algorithms for triangularization of large, sparse, and unsymmetric matrices are presented. ...
Texte intégral accessible uniquement aux membres de l'Université de LorraineThis dissertation treats...
A fundamental problem when adding column pivoting to the Householder QR fac- torization is that onl...
We introduce a parallel algorithm for computing the low rank approximation $A_k$ of a large matrix $...
The increasing complexity of modern computer architectures has greatly influenced algorithm design. ...
International audienceSolving linear equations of type Ax=b for large sparse systems frequently emer...
Abstract A Greedy Givens algorithm for computing the rank-1 updating of the QR decomposition is prop...
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