Abstract

We propose a parallel algorithm for computing a threshold incomplete LU (ILU) factorization. The main idea is to interleave a parallel fixed-point iteration that approximates an incomplete factorization for a given sparsity pattern with a procedure that adjusts the pattern. We describe and test a strategy for identifying nonzeros to be added and nonzeros to be removed from the sparsity pattern. The resulting pattern may be different and more effective than that of existing threshold ILU algorithms. Also in contrast to other parallel threshold ILU algorithms, much of the new algorithm has fine-grained parallelism.

Keywords

  1. incomplete factorization
  2. ILU
  3. parallel preconditioning

MSC codes

  1. 65F08
  2. 65F50
  3. 65Y05
  4. 68W10

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References

1.
H. Anzt, E. Chow, J. Saak, and J. Dongarra, Updating incomplete factorization preconditioners for model order reduction, Numer. Algorithms, 73 (2016), pp. 611--630.
2.
H. Anzt, M. Gates, J. Dongarra, M. Kreutzer, G. Wellein, and M. Köhler, Preconditioned Krylov solvers on GPUs, Parallel Comput., 68 (2017), pp. 32--44.
3.
A. Basermann, Parallel block ILUT/ILDLT preconditioning for sparse eigenproblems and sparse linear systems, Numer. Linear Algebra Appl., 7 (2000), pp. 635--648.
4.
M. Benzi, W. Joubert, and G. Mateescu, Numerical experiments with parallel orderings for ILU preconditioners, Electron. Trans. Numer. Anal., 8 (1999), pp. 88--114.
5.
M. Blum, R. W. Floyd, V. Pratt, R. L. Rivest, and R. E. Tarjan, Time bounds for selection, J. Comput. System Sci., 7 (1973), pp. 448--461.
6.
E. Chow, H. Anzt, and J. Dongarra, Asynchronous iterative algorithm for computing incomplete factorizations on GPUs, in Proceedings of 30th International Conference, ISC High Performance 2015, Lecture Notes in Comput. Sci. 9137, J. Kunkel and T. Ludwig, eds., Springer, New York, 2015, pp. 1--16.
7.
E. Chow and A. Patel, Fine-grained parallel incomplete LU factorization, SIAM J. Sci. Comput., 37 (2015), pp. C169--C193.
8.
E. Chow and Y. Saad, Experimental study of ILU preconditioners for indefinite matrices, J. Comput. Appl. Math., 85 (1997), pp. 387--414.
9.
E. Chow and Y. Saad, ILUS: An incomplete LU preconditioner in sparse skyline format, Internat. J. Numer. Methods Fluids, 25 (1997), pp. 739--748.
10.
T. A. Davis and Y. Hu, The University of Florida sparse matrix collection, ACM Trans. Math. Software, 38 (2011), pp. 1:1--1:25.
11.
S. Doi, On parallelism and convergence of incomplete LU factorizations, Appl. Numer. Math., 7 (1991), pp. 417--436.
12.
I. S. Duff and G. A. Meurant, The effect of ordering on preconditioned conjugate gradients, BIT, 29 (1989), pp. 635--657.
13.
D. Hysom and A. Pothen, A scalable parallel algorithm for incomplete factor preconditioning, SIAM J. Sci. Comput., 22 (2001), pp. 2194--2215.
14.
M. T. Jones and P. E. Plassmann, An improved incomplete Cholesky factorization, ACM Trans. Math. Softw., 21 (1995), pp. 5--17.
15.
G. Karypis and V. Kumar, Parallel threshold-based ILU factorization, in Proceedings of the ACM/IEEE Conference on Supercomputing, 1997, pp. 1--24.
16.
N. Li, Y. Saad, and E. Chow, Crout versions of $ILU$ for general sparse matrices, SIAM J. Sci. Comput., 25 (2003), pp. 716--728.
17.
X. S. Li and M. Shao, A supernodal approach to incomplete LU factorization with partial pivoting, ACM Trans. Math. Softw., 37 (2011), pp. 43:1--43:20.
18.
D. Lukarski, Parallel Sparse Linear Algebra for Multi-Core and Many-Core Platforms---Parallel Solvers and Preconditioners, Ph.D. thesis, Karlsruhe Institute of Technology, Germany, 2012.
19.
N. Munksgaard, Solving sparse symmetric sets of linear equations by preconditioned conjugate gradients, ACM Trans. Math. Softw., 6 (1980), pp. 206--219.
21.
E. L. Poole and J. M. Ortega, Multicolor ICCG methods for vector computers, SIAM J. Numer. Anal., 24 (1987), pp. 1394--1417.
22.
Y. Saad, ILUT: A dual threshold incomplete LU factorization, Numer. Linear Algebra Appl., 1 (1994), pp. 387--402.
23.
Y. Saad, Iterative Methods for Sparse Linear Systems, 2nd ed., SIAM, Philadelphia, 2003.
24.
S. Wang, E. de Sturler, and G. H. Paulino, Large-scale topology optimization using preconditioned Krylov subspace methods with recycling, Internat. J. Numer. Methods Engrg., 69 (2007), pp. 2441--2468.

Information & Authors

Information

Published In

cover image SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
Pages: C503 - C519
ISSN (online): 1095-7197

History

Submitted: 13 June 2016
Accepted: 7 May 2018
Published online: 12 July 2018

Keywords

  1. incomplete factorization
  2. ILU
  3. parallel preconditioning

MSC codes

  1. 65F08
  2. 65F50
  3. 65Y05
  4. 68W10

Authors

Affiliations

Funding Information

Office of Science https://doi.org/10.13039/100006132 : DE-SC0016513
Helmholtz Association https://doi.org/10.13039/501100009318 : VH-NG-1241

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