Abstract
In order to provide generallyap plicable iterative linear solvers for the communityof scientific computing the LINSOL program package has been designed. The focus of this package is on portability, robustness and on an efficient implementation on massivelyp arallel sys- tems. LINSOL uses iterative solvers as basic methods that are state of the art. Different normalization methods can be used to improve the convergence rates of the iterative solvers. Now preconditioners like the (in)complete Gaussian algorithm are being implemented. The paper is focussed on this type of algorithm. LINSOL is tuned to massively parallel systems with distributed memory. Therefore, the message passing pro- gramming style is used. LINSOL supports many matrix formats for the convenience of the users. Moreover, adaptive method selection schemes called polyalgorithms are implemented.
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Häfner, H., Schönauer, W., Weiss, R. (1999). Parallelization and Integration of the LU and ILU Algorithm in the LINSOL Program Package. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1999. Lecture Notes in Computer Science, vol 1662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48387-X_43
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DOI: https://doi.org/10.1007/3-540-48387-X_43
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