SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems

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In this paper, we present the main algorithmic features in the software package SuperLU{_}DIST, a distributed-memory sparse direct solver for large sets of linear equations. We give in detail our parallelization strategies, with focus on scalability issues, and demonstrate the parallel performance and scalability on current machines. The solver is based on sparse Gaussian elimination, with an innovative static pivoting strategy proposed earlier by the authors. The main advantage of static pivoting over classical partial pivoting is that it permits a priori determination of data structures and communication pattern for sparse Gaussian elimination, which makes it more scalable on distributed ... continued below

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Li, Xiaoye S. & Demmel, James W. March 27, 2002.

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In this paper, we present the main algorithmic features in the software package SuperLU{_}DIST, a distributed-memory sparse direct solver for large sets of linear equations. We give in detail our parallelization strategies, with focus on scalability issues, and demonstrate the parallel performance and scalability on current machines. The solver is based on sparse Gaussian elimination, with an innovative static pivoting strategy proposed earlier by the authors. The main advantage of static pivoting over classical partial pivoting is that it permits a priori determination of data structures and communication pattern for sparse Gaussian elimination, which makes it more scalable on distributed memory machines. Based on this a priori knowledge, we designed highly parallel and scalable algorithms for both LU decomposition and triangular solve and we show that they are suitable for large-scale distributed memory machines.

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OSTI as DE00836786

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  • Journal Name: ACM Transaction on Mathematical Software; Journal Volume: 29; Journal Issue: 2; Other Information: Submitted to ACM Transaction on Mathematical Software: Volume 29, No.2; Journal Publication Date: 6/2003

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  • Report No.: LBNL--49388
  • Grant Number: AC03-76SF00098
  • Office of Scientific & Technical Information Report Number: 836786
  • Archival Resource Key: ark:/67531/metadc785237

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  • March 27, 2002

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  • Dec. 3, 2015, 9:30 a.m.

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Li, Xiaoye S. & Demmel, James W. SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems, article, March 27, 2002; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc785237/: accessed October 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.