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doi: 10.1137/120902616
Summary: In this paper, we consider the computation in parallel of several entries of the inverse of a large sparse matrix. We assume that the matrix has already been factorized by a direct method and that the factors are distributed. Entries are efficiently computed by exploiting sparsity of the right-hand sides and the solution vectors in the triangular solution phase. We demonstrate that in this setting, parallelism and computational efficiency are two contrasting objectives. We develop an efficient approach and show its efficiency on a general purpose parallel multifrontal solver.
Parallel computing, computational efficiency, Calcul parallèle, sparse matrices, Sparse Linear Algebra, parallel algorithms, Parallel numerical computation, MUMPS, Direct numerical methods for linear systems and matrix inversion, Calcul parallèle, distribué et partagé, Computational methods for sparse matrices, Complexity and performance of numerical algorithms, [INFO.INFO-MS] Computer Science [cs]/Mathematical Software [cs.MS], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], distribué et partagé, direct methods for linear system and matrix inversion
Parallel computing, computational efficiency, Calcul parallèle, sparse matrices, Sparse Linear Algebra, parallel algorithms, Parallel numerical computation, MUMPS, Direct numerical methods for linear systems and matrix inversion, Calcul parallèle, distribué et partagé, Computational methods for sparse matrices, Complexity and performance of numerical algorithms, [INFO.INFO-MS] Computer Science [cs]/Mathematical Software [cs.MS], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], distribué et partagé, direct methods for linear system and matrix inversion
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