| J. Zhang. A multilevel dual reordering strategy for robust incomplete LU factorization of indefinite matrices. SIAM J. Matrix Anal. Appl., 22(3):925--947 (electronic), 2000. |
....is their excellent scalability with respect to mesh size. Their scope however is limited. A number of methods developed in the last decade have aspired to combine the good intrinsic properties of multigrid techniques and the generality of preconditioned Krylov subspace methods. Among these we cite [3, 5, 9, 7, 19, 22, 23, 26, 27, 28]. Multigrid methods are difficult to surpass when they work. However, their implementation requires multilevel grids and specialized tuning is often needed. The Algebraic Multigrid (AMG) methods were introduced in the seventies initially by Ruge and Stuben [18] to remedy these limitations. ....
J. Zhang. A multilevel dual reordering strategy for robust incomplete LU factorization of indefinite matrices. Technical Report 285-99, Department of Computer Science, University of Kentucky, 1999.
....convergence rate. The FIDAP and Flat matrices tested in Sections 5.2 and 5.3 have small or zero main diagonal entries. The poor convergence performance of both PBILU2 and SLU is mainly due to the instability associated with ILU factorizations of these matrices. Diagonal thresholding strategies [32, 38] can be employed in PBILU2 to exclude the rows with small diagonals from the submatrix B, so that its ILU factorization will be stable. The parallel implementation of diagonally thresholded PBILU2 will be investigated in our future study. We plan to extend our parallel two level block ILU ....
J. Zhang. A multilevel dual reordering strategy for robust incomplete LU factorization of indefinite matrices. Technical Report No. 285-99, Department of Computer Science, University of Kentucky, Lexington, KY, 1999. Submitted to SIAM J. Matrix Anal. Appl.
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J. Zhang. A multilevel dual reordering strategy for robust incomplete LU factorization of indefinite matrices. SIAM J. Matrix Anal. Appl., 22(3):925--947 (electronic), 2000.
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