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.
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References
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Aliaga, J.I., Bollhöfer, M., Martín, A.F., Quintana-Ortí, E.S. (2012). Parallelization of Multilevel ILU Preconditioners on Distributed-Memory Multiprocessors. In: Jónasson, K. (eds) Applied Parallel and Scientific Computing. PARA 2010. Lecture Notes in Computer Science, vol 7133. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28151-8_16
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DOI: https://doi.org/10.1007/978-3-642-28151-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28150-1
Online ISBN: 978-3-642-28151-8
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