A sparse QR-factorization algorithm SPARQR for coarse-grained parallel computations is described. The coefficient matrix, which is assumed to be general sparse, is reordered in an attempt to bring as many zero elements in the lower left corner as possible. The reordered matrix is then partitioned in
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QR factorization for the regularized least squares problem on hypercubes
β Scribed by Jianping Zhu
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 496 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0167-8191
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