Abstract
In this paper, we present a parallel multilevel ILU preconditioner implemented with OpenMP. We employ METIS partitioning algorithms to decompose the computation into concurrent tasks, which are then scheduled to threads. Concretely, we combine decompositions which obtain significantly more tasks than processors, and the use of dynamic scheduling strategies in order to reduce the thread's idle time, which it is shown to be the main source of overhead in our parallel algorithm. Experimental results on a shared-memory platform consisting of 16 processors report remarkable performance for our approach. © 2008 Springer Berlin Heidelberg.
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CITATION STYLE
Aliaga, J. I., Bollhöfer, M., Martín, A. F., & Quintana-Ortí, E. S. (2008). Design, tuning and evaluation of parallel multilevel ILU preconditioners. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5336 LNCS, pp. 314–327). https://doi.org/10.1007/978-3-540-92859-1_28
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