Abstract
The paper deals with the parallel computation of matrix factorization using graph partitioning-based domain decomposition. It is well-known that the partitioned graph may have both a small separator and well-balanced domains but sparse matrix decompositions on domains can be completely unbalanced.
In this paper we propose to enhance the iterative strategy for balancing the decompositions from [13] by graph-theoretical tools. We propose the whole framework for the graph repartitioning. In particular, new global and local reordering strategies for domains are discussed in more detail. We present both theoretical results for structured grids and experimental results for unstructured large-scale problems.
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Jurková, K., Tůma, M. (2010). Factorization-Based Graph Repartitionings. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2009. Lecture Notes in Computer Science, vol 5910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12535-5_92
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DOI: https://doi.org/10.1007/978-3-642-12535-5_92
Publisher Name: Springer, Berlin, Heidelberg
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