What is it about?

We introduce a software package called HIFIR for preconditioning sparse, unsymmetric, ill-conditioned, and potentially singular systems. HIFIR computes a hybrid incomplete factorization, which combines multilevel incomplete LU factorization with a truncated, rank-revealing QR factorization on the final Schur complement. It enables near-optimal preconditioners for consistent systems and enables flexible GMRES to solve inconsistent systems when coupled with iterative refinement.

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Why is it important?

Krylov subspace (KSP) methods, such as GMRES and BiCGSTAB, are widely used for solving large-scale sparse unsymmetric or indefinite linear systems, especially those arising from numerical discretizations of partial differential equations (PDEs). For relatively ill-conditioned matrices, the KSP methods can significantly benefit from a robust and efficient precondition. We demonstrate the effectiveness of HIFIR for ill-conditioned or singular systems arising from several applications, including the Helmholtz equation, linear elasticity, stationary incompressible Navier–Stokes equations, and time-dependent advection-diffusion equation.


Unlike previous software packages, HIFIR is designed to solve singular and near-singular (aka ill-conditioned) systems, including finding least-squares solutions for consistent singular systems, null-space vectors of singular matrices, and pseudoinverse solutions for inconsistent systems. This unique feature is backed by a new theory of epsilon-accurate AGI, and a new algorithm that combines multilevel incomplete LU factorization with an RRQR on the final Schur complement. We also introduce a new inverse-based rook pivoting into ILU, which improves the robustness and the overall efficiency of some ill-conditioned systems by significantly reducing the size of the final Schur complement for some systems

Xiangmin Jiao
Stony Brook University

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This page is a summary of: HIFIR: Hybrid Incomplete Factorization with Iterative Refinement for Preconditioning Ill-Conditioned and Singular Systems, ACM Transactions on Mathematical Software, September 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3536165.
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