Recently, I gave an invited talk at the "Lehrstuhl Numerische Mathematik für Höchstleistungsrechner (IANS)" at the University of Stuttgart that I would like to share here. The talk is about the parallel algebraic multigrid method (AMG) based on aggregation that I developed over the last years and showed some impressing scalability results on IBM's Blue Gene /P and on the Cray XE6.
The results on the Cray XE6 are contributed by Eike Müller. He also compared my solver with BoomerAMG and showed that e.g. for an anisotropic problem our AMG outperfoms it on large processor numbers. If you take into account that our AMG uses far less memory than BoomerAMG, this is really good news. Due to the memory requirements it is possible to compute problems with more than 130,000,000,000 degrees of freedom.
BTW: The algebraic multigrid code is under GPL with "runtime exception" and available in the module dune-istl from http://dune-project.org. Slides of talk "Massively Parallel Algebraic Multigrid in DUNE" (copyright: Markus Blatt 2012)
