The AMG4PSBLAS development team gladly announce the release of version 1.0 (release candidate 1 — rc1) of the package.
AMG4PSBLAS (Algebraic MultiGrid Preconditioners Package based on PSBLAS) is a package of parallel algebraic multilevel preconditioners included in the PSCToolkit (Parallel Sparse Computation Toolkit) software framework (https://psctoolkit.github.io/); its development is supported by the EU-H2020 EoCoE (Energy Oriented Center of Excellence) project, and the package has been selected by EU Innovation Radar as recent excellent innovation.
AMG4PSBLAS is designed to provide scalable and easy-to-use preconditioners in the context of the PSBLAS (Parallel Sparse Basic Linear Algebra Subprograms) parallel computing framework, to be used in conjunction with the PSBLAS Krylov solvers. The library uses a fully algebraic approach to generate a hierarchy of coarse-level matrices and operators; it includes a new parallel coupled aggregation algorithm exploiting maximum edge-weighted matchings. The preconditioners in AMG4PSBLAS can combine different types of AMG cycles with many smoothers and coarsest-level solvers. AMG4PSBLAS runs on most parallel computers, requiring only PSBLAS, the BLAS and MPI.
A GPU plugin for PSBLAS (available separately from https://psctoolkit.github.io/) enables the execution of AMG4PSBLAS applications on clusters with hybrid CPU/GPU nodes.