Effective and Robust Preconditioning of General SPD Matrices via Structured Incomplete Factorization

@inproceedings{Xin2017EffectiveAR,
  title={Effective and Robust Preconditioning of General SPD Matrices via Structured Incomplete Factorization},
  author={Jianlin Xia and Zixing Xin},
  year={2017}
}
For general symmetric positive definite (SPD) matrices, we present a framework for designing effective and robust black-box preconditioners via structured incomplete factorization. In a scaling-and-compression strategy, off-diagonal blocks are first scaled on both sides (by the inverses of the factors of the corresponding diagonal blocks) and then compressed into low-rank approximations. ULV-type factorizations are then computed. A resulting prototype preconditioner is always positive definite… CONTINUE READING