Abstract
The aim is to present a new data distribution of triangular matrices that provides steady distribution of blocks among processes and reduces memory wasting compared to the standard block-cyclic data layout used in the ScaLAPACK library for dense matrix computations. A new algorithm for solving triangular systems of linear equations is also introduced. The results of experiments performed on a cluster of Itanium 2 processors and Cray X1 show that in some cases, the new method is faster than corresponding PBLAS routines PSTRSV and PSTRSM.
The work has been sponsored by the KBN grant 6T11 2003C/06098. The use of Cray X1 from the Interdisciplinary Center for Mathematical and Computational Modeling (ICM) of the Warsaw University is kindly acknowledged.
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Stpiczyński, P. (2007). New Data Distribution for Solving Triangular Systems on Distributed Memory Machines. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_71
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DOI: https://doi.org/10.1007/978-3-540-75755-9_71
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