Parallel algorithms and condition estimators for standard and generalized triangular sylvester-type matrix equations

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Abstract

We discuss parallel algorithms for solving eight common standard and generalized triangular Sylvester-type matrix equation. Our parallel algorithms are based on explicit blocking, 2D block-cyclic data distribution of the matrices and wavefront-like traversal of the right hand side matrices while solving small-sized matrix equations at different nodes and updating the rest of the right hand side using level 3 operations. We apply the triangular solvers in condition estimation, developing parallel sep-1-estimators. Some experimental results are presented. © Springer-Verlag Berlin Heidelberg 2007.

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Granat, R., & Kågström, B. (2007). Parallel algorithms and condition estimators for standard and generalized triangular sylvester-type matrix equations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4699 LNCS, pp. 127–136). Springer Verlag. https://doi.org/10.1007/978-3-540-75755-9_16

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