Veranstalter: Graduiertenschule Computational Engineering
Referent: Prof. Dr. Matthias Bollhöfer
Many application problems that lead to solving linear systems make use of preconditioned Krylov subspace solvers to compute their solution. Among the most popular preconditioning approaches are incomplete factorization methods either as single-level approaches or within a multilevel framework. We will present a block incomplete triangular factorization that is based on skilfully blocking the system initially and throughout the factorization. This approach allows for the use of cache-optimized dense matrix kernels such level-3 BLAS or LAPACK. We will demonstrate how this block approach may signifcantly outperform the scalar method on modern architectures, paving the way for its prospective use inside various multilevel incomplete factorization approaches or other applications where the core part relies on an incomplete factorization.