Abstract
In this paper we investigate the parallelization of the ILUPACK library for the solution of sparse linear systems on distributed-memory multiprocessors. The parallelization approach employs multilevel graph partitioning algorithms in order to identify a set of concurrent tasks and their dependencies, which are then statically mapped to processors. Experimental results on a cluster of Intel QuadCore processors report remarkable speed-ups. © 2012 Springer-Verlag.
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CITATION STYLE
Aliaga, J. I., Bollhöfer, M., Martín, A. F., & Quintana-Ortí, E. S. (2012). Parallelization of multilevel ILU preconditioners on distributed-memory multiprocessors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7133 LNCS, pp. 162–172). https://doi.org/10.1007/978-3-642-28151-8_16
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