Name
Abstract | ||
|---|---|---|
Krylov space methods like conjugate gradient and GMRES are efficient and parallelizable approaches for solving huge and sparse linear systems of equations. But as condition numbers are increasing polynomially with problem size sophisticated preconditioning techniques are essential building blocks. However, many preconditioning approaches like Gauss-Seidel/SSOR and ILU are based on sequential algorithms. Introducing parallelism for preconditioners is mostly hampering mathematical efficiency. In the era of multi-core and many-core processors like GPUs there is a strong need for scalable and fine-grained parallel preconditioning approaches. In the framework of the multi-platform capable finite element package HiFlow3 we are investigating multi-coloring techniques for block Gauss-Seidel type preconditioners. Our approach proves efficiency and scalability across hybrid multi-core and GPU platforms. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-21878-1_48 | Euro-Par Workshops |
Keywords | Field | DocType |
mathematical efficiency,hybrid multi-core,introducing parallelism,block gauss-seidel type preconditioners,fine-grained parallel preconditioning approach,multi-core cpus,scalable multi-coloring preconditioning,gpu platform,preconditioning approach,condition number,krylov space method,sophisticated preconditioning technique | Parallelizable manifold,Conjugate gradient method,Linear system,Generalized minimal residual method,Computer science,Parallel computing,Finite element method,Multi-core processor,Gauss–Seidel method,Scalability | Conference |
Volume | ISSN | Citations |
6586 | 0302-9743 | 4 |
PageRank | References | Authors |
0.71 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent Heuveline | 1 | 179 | 30.51 |
| Dimitar Lukarski | 2 | 39 | 5.39 |
| Jan-Philipp Weiss | 3 | 46 | 5.37 |