Domain decomposition: parallel multilevel methods for elliptic partial differential equations
Domain decomposition: parallel multilevel methods for elliptic partial differential equations
Level 3 basic linear algebra subprograms for sparse matrices: a user-level interface
ACM Transactions on Mathematical Software (TOMS)
A Supernodal Approach to Sparse Partial Pivoting
SIAM Journal on Matrix Analysis and Applications
An Asynchronous Parallel Supernodal Algorithm for Sparse Gaussian Elimination
SIAM Journal on Matrix Analysis and Applications
A Restricted Additive Schwarz Preconditioner for General Sparse Linear Systems
SIAM Journal on Scientific Computing
PSBLAS: a library for parallel linear algebra computation on sparse matrices
ACM Transactions on Mathematical Software (TOMS)
Parallel smoothed aggregation multigrid: aggregation strategies on massively parallel machines
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
MPI-The Complete Reference, Volume 1: The MPI Core
MPI-The Complete Reference, Volume 1: The MPI Core
ACM Transactions on Mathematical Software (TOMS)
BoomerAMG: a parallel algebraic multigrid solver and preconditioner
Applied Numerical Mathematics - Developments and trends in iterative methods for large systems of equations—in memoriam Rüdiger Weiss
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Algorithm 832: UMFPACK V4.3---an unsymmetric-pattern multifrontal method
ACM Transactions on Mathematical Software (TOMS)
An overview of the Trilinos project
ACM Transactions on Mathematical Software (TOMS) - Special issue on the Advanced CompuTational Software (ACTS) Collection
An Introduction to Algebraic Multigrid
Computing in Science and Engineering
2LEV-D2P4: a package of high-performance preconditioners for scientific and engineering applications
Applicable Algebra in Engineering, Communication and Computing
On the development of PSBLAS-based parallel two-level Schwarz preconditioners
Applied Numerical Mathematics
Performance Optimization and Modeling of Blocked Sparse Kernels
International Journal of High Performance Computing Applications
Using GPUs to improve multigrid solver performance on a cluster
International Journal of Computational Science and Engineering
A New Petrov-Galerkin Smoothed Aggregation Preconditioner for Nonsymmetric Linear Systems
SIAM Journal on Scientific Computing
Extending PSBLAS to build parallel schwarz preconditioners
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Design patterns for scientific computations on sparse matrices
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing
Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003
ACM Transactions on Mathematical Software (TOMS)
Performance analysis of parallel Schwarz preconditioners in the LES of turbulent channel flows
Computers & Mathematics with Applications
Design patterns for sparse-matrix computations on hybrid CPU/GPU platforms
Scientific Programming
| Hi-index | 0.00 |
Domain decomposition ideas have long been an essential tool for the solution of PDEs on parallel computers. In recent years many research efforts have been focused on recursively employing domain decomposition methods to obtain multilevel preconditioners to be used with Krylov solvers. In this context, we developed MLD2P4 (MultiLevel Domain Decomposition Parallel Preconditioners Package based on PSBLAS), a package of parallel multilevel preconditioners that combines additive Schwarz domain decomposition methods with a smoothed aggregation technique to build a hierarchy of coarse-level corrections in an algebraic way. The design of MLD2P4 was guided by objectives such as extensibility, flexibility, performance, portability, and ease of use. They were achieved by following an object-based approach while using the Fortran 95 language, as well as by employing the PSBLAS library as a basic framework. In this article, we present MLD2P4 focusing on its design principles, software architecture, and use.