Scalable Approximate Selected Inversion Based on Single-Level Incomplete $LDL^T$ Factorization and Spectral Corrections for Large Sparse Systems
Four parallel numerical techniques for computing entries of the inverse of large sparse symmetric systems grounded in incomplete $LDL^T$ (ILDL) factorizations are introduced and a low-rank correction based on eigenvector updates is employed, providing an alternative to tightening the drop tolerance.