Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning

doi:10.1016/j.jpdc.2018.04.017

Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning

2018-09-01

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DOI：10.1016/j.jpdc.2018.04.017

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When using incomplete factorization preconditioners with an iterative method to solve large sparse linear systems, each application of the preconditioner involves solving two sparse triangular systems. These triangular systems are challenging to solve efficiently on computers with high levels of concurrency. On such computers, it has recently been proposed to use Jacobi iterations, which are highly parallel, to approximately solve the triangular systems from incomplete factorizations. The effectiveness of this approach, however, is problem-dependent: the Jacobi iterations may not always converge quickly enough for all problems. Thus, as a necessary and important step to evaluate this approach, we experimentally test the approach on a large number of realistic symmetric positive definite problems. We also show that by using block Jacobi iterations, we can extend the range of problems for which such an approach can be effective. For block Jacobi iterations, it is essential for the blocking to be cognizant of the matrix structure. (C) 2018 Elsevier Inc. All rights reserved.

Keywords:

Sparse linear systems

Triangular solves

Iterative solvers

Preconditioning

Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning

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