Sparse Householder QR factorization on a mesh
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Sparse Householder QR factorization on a meshFecha
1996-01Cita bibliográfica
R. Doallo, J. Tourino and E. L. Zapata, "Sparse Householder QR factorization on a mesh," Proceedings of 4th Euromicro Workshop on Parallel and Distributed Processing, Braga, Portugal, 1996, pp. 33-39. doi: 10.1109/EMPDP.1996.500566
Resumen
[Abstract] We analyze the parallelization of QR factorization by means of Householder transformations. This parallelization is carried out on a machine with a mesh topology (a 2-D torus to be more precise). We use a cyclic distribution of the elements of the sparse matrix M we want to decompose over the processors. Each processor represents the nonzero elements of its part of the matrix by a one-dimensional doubly linked list data structure. Then, we describe the different procedures that constitute the parallel algorithm. As an application of QR factorization, we concentrate on the least squares problem and finally we present an evaluation of the efficiency of this algorithm for a set of test matrices from the Harwell-Boeing sparse matrix collection.
Palabras clave
Sparse matrices
Matrix decomposition
Parallel algorithms
Least squares methods
Equations
Topology
Data structures
System testing
Fluid dynamics
Chemistry
Matrix decomposition
Parallel algorithms
Least squares methods
Equations
Topology
Data structures
System testing
Fluid dynamics
Chemistry
Descripción
This is a post-peer-review, pre-copyedit version of an article published in Proceedings of 4th Euromicro Workshop on Parallel and Distributed Processing. The final authenticated version is available online at: http://dx.doi.org/10.1109/EMPDP.1996.500566.
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ISBN
0-8186-7376-1