Parallel Sparse Modified Gram-Schmidt QR Decomposition
Use this link to cite
http://hdl.handle.net/2183/22369Collections
- Investigación (FIC) [1615]
Metadata
Show full item recordTitle
Parallel Sparse Modified Gram-Schmidt QR DecompositionDate
1996Citation
Doallo R., Fraguela B.B., Touriño J., Zapata E.L. (1996) Parallel sparse modified Gram-Schmidt QR decomposition. In: Liddell H., Colbrook A., Hertzberger B., Sloot P. (eds) High-Performance Computing and Networking. HPCN-Europe 1996. Lecture Notes in Computer Science, vol 1067. Springer, Berlin, Heidelberg
Abstract
[Abstract] We present a parallel computational method for the QR decomposition with column pivoting of a sparse matrix by means of Modified Gram-Schmidt orthogonalization. Nonzero elements of the matrix M to be decomposed are stored in a one-dimensional doubly linked list data structure. We discuse a strategy to reduce fill-in in order to get memory savings and decrease the computation times. As an application of QR decomposition, we describe the least squares problem. This algorithm was designed for a message passing multiprocessor and has been evaluated on a Cray T3D, using the Harwell-Boeing sparse matrix collection.
Keywords
Nonzero element
Sequential algorithm
Sparse matrice
Little square problem
Pivot element
Sequential algorithm
Sparse matrice
Little square problem
Pivot element
Description
This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: https://doi.org/10.1007/3-540-61142-8_609
Editor version
ISSN
0302-9743
1611-3349
1611-3349
ISBN
978-3-540-61142-4 978-3-540-49955-8