Abstract
We investigate performance characteristics for the LU factorization of large matrices with various sparsity patterns. We consider supernodal right-looking parallel factorization on a two dimensional grid of processors, making use of static pivoting. We develop a performance model and we validate it using the implementation in SuperLU_DIST, the real matrices and the IBM Power3 machine at NERSC. We use this model to obtain performance bounds on parallel computers, to perform scalability analysis and to identify performance bottlenecks. We also discuss the role of load balance and data distribution in this approach.
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Grigori, L., Li, X.S. (2006). Performance Analysis of Parallel Right-Looking Sparse LU Factorization on Two Dimensional Grids of Processors. 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_93
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DOI: https://doi.org/10.1007/11558958_93
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29067-4
Online ISBN: 978-3-540-33498-9
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