Table of Contents

Official website:

1 MaPHyS

Massively Parallel Hybrid Solver

MaPHyS (Massively Parallel Hybrid Solver) is a software package whose prototype was initially developed in the framework of the PhD thesis of Azzam Haidar (CERFACS) and further consolidated thanks to the ANR-CIS Solstice funding. This parallel linear solver couples direct and iterative approaches. The underlying idea is to apply to general unstructured linear systems domain decomposition ideas developed for the solution of linear systems arising from PDEs. The interface problem, associated with the so called Schur complement system, is solved using a block preconditioner with overlap between the blocks that is referred to as Algebraic Additive Schwarz. To cope with the possible lack of coarse grid mechanism that enables one to keep constant the number of iterations when the number of blocks is increased, the solver exploits two levels of parallelism (between the blocks and within the treatment of the blocks). This enables us to exploit a large number of processors with a moderate number of blocks which ensures a reasonable convergence behaviour. The current prototype code will be further consolidated to end-up with a high performance software package to be made freely available to the scientific community.

(extracted from HiePaCS' Proposal, a joint Project-Team with University of Bordeaux and CNRS (LaBRI UMR 5800) and Research Action between INRIA and CERFACS)

2 Installation

MaPHyS has many dependencies. We strongly recommand to use our version of SPACK to install MaPHyS and its dependencies easily. The procedure is described in

If you want to install MaPHyS on a cluster, you should take a look at

3 Maphys versions and documentations

Warning: installation of MaPHyS from the tarball is possible but not recommanded. Check section 2.

Version Tarball Documentation (recommended) Tarball Documentation-0.9.4 Tarball Documentation-0.9.4 Tarball Documentation-0.9.4
0.9.3 Tarball Documentation-0.9.3

4 Links

Author: HiePACS

Created: 2017-01-26 Thu 18:31