Abstract
In this paper, we describe a parallel direct solver for general sparse systems of linear equations that has recently been included in the Watson Sparse Matrix Package (WSMP) [7]. This solver utilizes both shared- and distributed- memory parallelism in the same program and is designed for a hierarchical parallel computer with network-interconnected SMP nodes. We compare the WSMP solver with two similar well known solvers: MUMPS [2] and Super_LU Dist [10]. We show that the WSMP solver achieves significantly better performance than both these solvers based on traditional algorithms and is more numerically robust than Super_LU Dist . We had earlier shown [8] that MUMPS and Super_LU Dist are amongst the fastest distributed-memory general sparse solvers available.
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© 2006 Springer-Verlag Berlin Heidelberg
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Gupta, A. (2006). A Shared- and Distributed-Memory Parallel Sparse Direct Solver. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2004. Lecture Notes in Computer Science, vol 3732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558958_94
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DOI: https://doi.org/10.1007/11558958_94
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29067-4
Online ISBN: 978-3-540-33498-9
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