Abstract
PARASPAR is a package for the solution of linear algebraic systems whose coefficient matrices are large and sparse. Linear least squares problems can also be treated by PARASPAR (using the method of augmentation). Both direct methods and preconditioned iterative procedures are used. The direct methods are based on the classical Gaussian elimination with three different pivotal strategies. The iterative methods used are a modified ORTHOMIN algorithm, CGS, BI-CGSTAB and TFQMR. The preconditioners for all iterative algorithms are calculated by using an approximate LU factorization, which is obtained by dropping small non-zero elements during the Gaussian elimination. If the preconditioners are not sufficiently accurate (and, therefore, the iterative process is either divergent or the convergence is very slow), then an attempt to increase the accuracy of the preconditioner can automatically be performed.
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F. L. Alvarado, A. Pothen and R. Schreiber: “Highly parallel sparse triangular solution”. Report No. CS-92-09, Department of Computer Science, The Pennsylvania State University, University Park, PA 16802, USA, 1992.
E. Anderson, Z. Bai, C. Bischof, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, S. Ostrouchov and D. Sorensen: “LAPACK: Users' Guide” SIAM (Society for Industrial and Applied Mathematics), Philadelphia, 1992.
E. Anderson and Y. Saad: “Preconditioned conjugate gradient methods for general sparse matrices on shared memory machines”. In: “PARALLEL PROCESSING FOR SCIENTIFIC COMPUTING” (G. Rodrigue, ed.), pp. 88–92. Society for Industrial and Applied Mathematics, Philadelphia, 1989.
M. Arioli, I. S. Duff and D. Ruiz: “Stopping criteria for iterative solvers”. Report No. RAL-91-057. Rutherford Appleton Laboratory, Oxon OX11 0QX, ENGLAND, 1991.
T. A. Davis and P.-C. Yew: “A nondeterministic parallel algorithm for general unsymmetric sparse LU factorization”. SIAM J. Matrix. Anal. Appl., 3 (1990), 383–402.
D. S. Dodson and J. G. Lewis: “Proposed sparse extensions to the basic linear algebra subprograms”. ACM SIGNUM Newsletter, 20 (1985), 22–25.
J. J. Dongarra and S. C. Eisenstat: “Squeezing the most out of an algorithm in CRAY FORTRAN”. ACM Trans. Math. Software, 10 (1984), 219–230.
J. J. Dongarra, F. G. Gustavson and A. Karp: “Implementing linear algebra algorithms for dense matrices on a vector pipeline machine”. SIAM Rev., 26 (1984), 91–112.
I. S. Duff and J. K. Reid: “MA48: a FORTRAN code for direct solution for sparse unsymmetric linear systems of equations equations”. Report No. RAL-93-072 Central Computing Department, Rutherford Appleton Laboratory. Oxon OX11 0QX, ENGLAND, 1993.
I. S. Duff, R. G. Grimes and J. C. Lewis: “Sparse matrix test problems”. ACM Trans. Math. Software, 15 (1989), 1–14.
S. C. Eisenstat, H. C. Elman and M. H. Schultz: “Variational methods for nonsymmetric systems of linear equations”. SIAM J. Numer. Anal., 20 (1983), 345–357.
S. C. Eisenstat, M. C. Gursky, M. H. Schultz and A. H. Sherman: “The YALE sparse matrix package: The symmetric codes”. Internat. J. Numer. Meth. Engng., 18(1982), 1145–1151.
R. W. Freund: “A transpose free quasi minimal resudual algorithm for non-hermitian linear systems”. SIAM J. Sci. Comput., 14 (1993), 470–482.
K. A. Gallivan, P. C. Hansen, Tz. Ostromski and Z. Zlatev: “A locally optimized reordering algorithm and its application to a parallel sparse linear system solver”. Report UNIC-93-07. The Danish Computer Centre for Research and Education, Technical University of Denmark, Bldg. 305. DK-2800 Lyngby, DENMARK, 1993.
K. A. Gallivan, A. H. Sameh and Z. Zlatev: “Solving general sparse linear systems using conjugate gradient-type methods”. In: “PROCEEDINGS OF THE 1990 INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, June 11–15 1990, Amsterdam, The Netherlands”. ACM Press, New York, 1990.
K. A. Gallivan, A. H. Sameh and Z. Zlatev: “A parallel hybrid sparse linear system solver”. Computing Systems in Engineering, 1 (1990), 183–195.
J. A. George and J. W. Liu: “Computer solution of large sparse positive definite systems”. Prentice-Hall, Englewood Cliffs, N. J., 1981.
J. A. George and E. Ng: “Symbolic factorization for sparse Gaussian elimintion with partial pivoting”. SIAM J. Sci. Statist. Comput., 8(1987), 877–898.
J. R. Gilbert and T. Peierls: “Sparse partial pivoting in time proportional to arithmetic operations”. SIAM J. Sci. Statist. Comput., 9(1988), 862–874.
Y. Saad and M. H. Schultz: “CMRES: A generalized minimal residual algorithm for solving nonsymmetric linear systems”. SIAM J. Sci. Statist. Comput., 7(1986), 856–869.
A. van der Sluis and H. A. van der Vorst: “The rate of convergence of conjugate gradients”. Numer. Math., 48(1986), 543–560.
A. van der Sluis and H. A. van der Vorst: “The convergence behaviour of Ritz values in the presence of close eigenvalues”. Report No 86-08. Department of Mathematics and Informatics, Delft University of Technology, Julianalaan 132, 2628 BL Delft, Netherlands, 1986.
P. Sonneveld: “CGS, a fast Lanzos-type solver for nonsymmetric linear systems”. SIAM J. Sci. Statist. Comput., 10 (1989), 36–52.
A. F. van der Stappen, R. H. Bisseling and J. G. G. van der Vorst: “Parallel sparse LU decomposition on a mesh network of transputers”. SIAM J. Matrix Anal. Appl., 14(1993), 853–879.
P. K. W. Vinsome: “Orthomin, an iterative method for solving sparse sets of simultaneous linear equations”. In: “PROCEEDINGS OF THE FOURTH SYMPOSIUM ON RESERVOIR SIMULATION”, pp. 140–159. Society of Petroleum Engineers of AIME, 1076.
H. A. van der Vorst: “BI-CGSTAB: a fast and smoothly converging variant of BI-CG for the solution of nonsymmetric linear systems”. SIAM J. Sci. Statist. Comput., 13(1992), 631–644.
Z. Zlatev: “On some pivotal strategies in Gaussian elimination by sparse technique”. SIAM J. Numer. Anal., 17(1980), 18–30.
Z. Zlatev: “Use of iterative refinement in the solution of sparse linear systems”. SIAM J. Numer. Anal., 19(1982), 381–399.
Z. Zlatev: “Computational methods for general sparse matrices”. Kluwer Academic Publishers, Dordrecht-Toron to-London, 1991.
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© 1994 Springer-Verlag Berlin Heidelberg
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Zlatev, Z., Waśniewski, J. (1994). PARASPAR: Parallel solvers for sparse linear algebraic systems. In: Dongarra, J., Waśniewski, J. (eds) Parallel Scientific Computing. PARA 1994. Lecture Notes in Computer Science, vol 879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0030181
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DOI: https://doi.org/10.1007/BFb0030181
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