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Local Pivoting for Sparse Factorizations on Multiprocessors  (Make Corrections)  
Juan Tourino, Ramon Doallo



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Abstract: Many linear algebra algorithms require explicit row/column swapping mainly when pivoting operations are involved. Assuming an MIMD distributed-memory environment, these pivoting operations imply a communication overhead between the processors which store the corresponding rows/columns to be swapped. These communications suppose an appreciable bottleneck in the algorithms and reduce parallelism. (Update)

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BibTeX entry:   (Update)

@misc{ tourino-local,
  author = "Juan Tourino and Ramon Doallo",
  title = "Local Pivoting for Sparse Factorizations on Multiprocessors",
  url = "citeseer.ist.psu.edu/683743.html" }
Citations (may not include all citations):
2441   The Johns Hopkins University Press (context) - Golub, Van Loan - 1989
88   User's Guide for the Harwell-Boeing Sparse Matrix Collection (context) - Duff, Grimes et al. - 1992
21   ScaLAPACK: a Portable Linear Algebra Library for Distributed.. - Choi, Demmel et al. - 1995
7   Parallel Sparse Modified Gram-Schmidt QR Decomposition - Doallo, Fraguela et al. - 1996
7   Exploiting Locality on Parallel Sparse Matrix Computations - Trabado, Zapata - 1995
2   Parallelization and Compilation Issues for Sparse QR Algorit.. (context) - no - 1997
2   An Approach to Decrease Fill-in in Sparse Orthogonalizations.. - no, Doallo - 1996

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