Open Access
2014 MRILDU: An Improvement to ILUT Based on Incomplete LDU Factorization and Dropping in Multiple Rows
Jian-Ping Wu, Huai-Fa Ma
J. Appl. Math. 2014(SI12): 1-9 (2014). DOI: 10.1155/2014/467672


We provide an improvement MRILDU to ILUT for general sparse linear systems in the paper. The improvement is based on the consideration that relatively large elements should be kept down as much as possible. To do so, two schemes are used. Firstly, incomplete LDU factorization is used instead of incomplete LU. Besides, multiple rows are computed at a time, and then dropping is applied to these rows to extract the relatively large elements in magnitude. Incomplete LDU is not only fairer when there are large differences between the elements of factors L and U, but also more natural for the latter dropping in multiple rows. And the dropping in multiple rows is more profitable, for there may be large differences between elements in different rows in each factor. The provided MRILDU is comparable to ILUT in storage requirement and computational complexity. And the experiments for spare linear systems from UF Sparse Matrix Collection, inertial constrained fusion simulation, numerical weather prediction, and concrete sample simulation show that it is more effective than ILUT in most cases and is not as sensitive as ILUT to the parameter p, the maximum number of nonzeros allowed in each row of a factor.


Download Citation

Jian-Ping Wu. Huai-Fa Ma. "MRILDU: An Improvement to ILUT Based on Incomplete LDU Factorization and Dropping in Multiple Rows." J. Appl. Math. 2014 (SI12) 1 - 9, 2014.


Published: 2014
First available in Project Euclid: 27 February 2015

zbMATH: 07131615
Digital Object Identifier: 10.1155/2014/467672

Rights: Copyright © 2014 Hindawi

Vol.2014 • No. SI12 • 2014
Back to Top