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Abstract: Sparse Gaussian Elimination on High Performance Computers by XiaoyeS.Li Doctor of Philosophy in Computer Science University of California at Berkeley James W. Demmel, Chair This dissertation presents new techniques for solving large sparse unsymmetric linear systems on high performance computers, using Gaussian elimination with partial pivoting. The e#ciencies of the new algorithms are demonstrated for matrices from various #elds and for a variety of high performance machines. In the... (Update)
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...the storage necessary for the QR or LU factorization. In particular, our work was motivated by the LU factorization code SuperLU [3, 4, 17]. Both the sequential and parallel versions of SuperLU use the column elimination tree to cluster 1 In this factorization matrix A can...
...solvers in a uniform way. We have integrated numerous solvers, including some from LAPACK [1] ARPACK [8] PETSc [2] Aztec [7] SuperLU [9] and MA28 [5] Each of these packages has its own set of options and settings. We have used the PDF, as described in Section 2 to make...
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BibTeX entry: (Update)
X. Li, Sparse Gaussian Elimination on High Performance Computers , PhD thesis, CS, UC Berkeley, 1996. http://citeseer.ist.psu.edu/li96sparse.html More
@techreport{ li97sparse,
author = "Xiaoye S. Li",
title = "Sparse Gaussian Elimination on High Performance Computers",
number = "UT-CS-97-368",
year = "1997",
url = "citeseer.ist.psu.edu/li96sparse.html" }
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