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Published in: Journal of Scientific Computing 2/2016

11-01-2016

Analysis and Practical Use of Flexible BiCGStab

Authors: Jie Chen, Lois C. McInnes, Hong Zhang

Published in: Journal of Scientific Computing | Issue 2/2016

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Abstract

A flexible version of the BiCGStab algorithm for solving a linear system of equations is analyzed. We show that under variable preconditioning, the perturbation to the outer residual norm is of the same order as that to the application of the preconditioner. Hence, in order to maintain a similar convergence behavior to BiCGStab while reducing the preconditioning cost, the flexible version can be used with a moderate tolerance in the preconditioning Krylov solves. We explored the use of flexible BiCGStab in a large-scale reacting flow application, PFLOTRAN, and showed that the use of a variable multigrid preconditioner significantly accelerates the simulation time on extreme-scale computers using \(O(10^4)\)\(O(10^5)\) processor cores.

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Literature
4.
go back to reference Axelsson, O., Vassilevski, P.S.: A black box generalized conjugate gradient solver with inner iterations and variable-step preconditioning. SIAM J. Matrix Anal. Appl. 12(4), 625–644 (1991)MathSciNetCrossRefMATH Axelsson, O., Vassilevski, P.S.: A black box generalized conjugate gradient solver with inner iterations and variable-step preconditioning. SIAM J. Matrix Anal. Appl. 12(4), 625–644 (1991)MathSciNetCrossRefMATH
5.
go back to reference Balay, S., Abhyankar, S., Adams, M.F., Brown, J., Brune, P., Buschelman, K., Eijkhout, V., Gropp, W.D., Kaushik, D., Knepley, M.G., McInnes, L.C., Rupp, K., Smith, B.F., Zhang, H.: PETSc users manual. Tech. Rep. ANL-95/11-Revision 3.5, Argonne National Laboratory (2014) URL http://www.mcs.anl.gov/petsc Balay, S., Abhyankar, S., Adams, M.F., Brown, J., Brune, P., Buschelman, K., Eijkhout, V., Gropp, W.D., Kaushik, D., Knepley, M.G., McInnes, L.C., Rupp, K., Smith, B.F., Zhang, H.: PETSc users manual. Tech. Rep. ANL-95/11-Revision 3.5, Argonne National Laboratory (2014) URL http://​www.​mcs.​anl.​gov/​petsc
7.
go back to reference Bouras, A., Frayssé, V.: Inexact matrix-vector products in Krylov methods for solving linear systems: a relaxation strategy. SIAM J. Matrix Anal. Appl. 26(3), 660–678 (2005)MathSciNetCrossRefMATH Bouras, A., Frayssé, V.: Inexact matrix-vector products in Krylov methods for solving linear systems: a relaxation strategy. SIAM J. Matrix Anal. Appl. 26(3), 660–678 (2005)MathSciNetCrossRefMATH
8.
go back to reference Bridges, P.G., Ferreira, K.B., Heroux, M.A., Hoemmen, M.: Fault-tolerant linear solvers via selective reliability. CoRR arXiv:1206.1390 (2012) Bridges, P.G., Ferreira, K.B., Heroux, M.A., Hoemmen, M.: Fault-tolerant linear solvers via selective reliability. CoRR arXiv:​1206.​1390 (2012)
10.
11.
12.
go back to reference Eshof, Jv, Sleijpen, G.L.G.: Inexact Krylov subspace methods for linear systems. SIAM J. Matrix Anal. Appl. 26(1), 125–153 (2004)MathSciNetCrossRefMATH Eshof, Jv, Sleijpen, G.L.G.: Inexact Krylov subspace methods for linear systems. SIAM J. Matrix Anal. Appl. 26(1), 125–153 (2004)MathSciNetCrossRefMATH
15.
go back to reference Giladi, E., Golub, G.H., Keller, J.B.: Inner and outer iterations for the Chebyshev algorithm. SIAM J. Numer. Anal. 35, 300–319 (1995)MathSciNetCrossRefMATH Giladi, E., Golub, G.H., Keller, J.B.: Inner and outer iterations for the Chebyshev algorithm. SIAM J. Numer. Anal. 35, 300–319 (1995)MathSciNetCrossRefMATH
16.
go back to reference Golub, G.H., Ye, Q.: Inexact preconditioned conjugate gradient method with inner-outer iteration. SIAM J. Sci. Comput. 21(4), 1305–1320 (1999)MathSciNetCrossRefMATH Golub, G.H., Ye, Q.: Inexact preconditioned conjugate gradient method with inner-outer iteration. SIAM J. Sci. Comput. 21(4), 1305–1320 (1999)MathSciNetCrossRefMATH
17.
go back to reference Keyes, D.E., McInnes, L.C., Woodward, C., Gropp, W., Myra, E., Pernice, M., Bell, J., Brown, J., Clo, A., Connors, J., Constantinescu, E., Estep, D., Evans, K., Farhat, C., Hakim, A., Hammond, G., Hansen, G., Hill, J., Isaac, T., Jiao, X., Jordan, K., Kaushik, D., Kaxiras, E., Koniges, A., Lee, K., Lott, A., Lu, Q., Magerlein, J., Maxwell, R., McCourt, M., Mehl, M., Pawlowski, R., Randles, A.P., Reynolds, D., Rivière, B., Rüde, U., Scheibe, T., Shadid, J., Sheehan, B., Shephard, M., Siegel, A., Smith, B., Tang, X., Wilson, C., Wohlmuth, B.: Multiphysics simulations: challenges and opportunities. Int. J. High Perform. Comput. Appl. 27(1), 4–83 (2013). URL http://www.ipd.anl.gov/anlpubs/2012/01/72183.pdf Keyes, D.E., McInnes, L.C., Woodward, C., Gropp, W., Myra, E., Pernice, M., Bell, J., Brown, J., Clo, A., Connors, J., Constantinescu, E., Estep, D., Evans, K., Farhat, C., Hakim, A., Hammond, G., Hansen, G., Hill, J., Isaac, T., Jiao, X., Jordan, K., Kaushik, D., Kaxiras, E., Koniges, A., Lee, K., Lott, A., Lu, Q., Magerlein, J., Maxwell, R., McCourt, M., Mehl, M., Pawlowski, R., Randles, A.P., Reynolds, D., Rivière, B., Rüde, U., Scheibe, T., Shadid, J., Sheehan, B., Shephard, M., Siegel, A., Smith, B., Tang, X., Wilson, C., Wohlmuth, B.: Multiphysics simulations: challenges and opportunities. Int. J. High Perform. Comput. Appl. 27(1), 4–83 (2013). URL http://​www.​ipd.​anl.​gov/​anlpubs/​2012/​01/​72183.​pdf
19.
go back to reference Mills, R.T., Sripathi, V., Mahinthakumar, G., Hammond, G., Lichtner, P.C., Smith, B.F.: Engineering PFLOTRAN for scalable performance on Cray XT and IBM BlueGene architectures. In: Proceedings of SciDAC 2010 Annual Meeting (2010) Mills, R.T., Sripathi, V., Mahinthakumar, G., Hammond, G., Lichtner, P.C., Smith, B.F.: Engineering PFLOTRAN for scalable performance on Cray XT and IBM BlueGene architectures. In: Proceedings of SciDAC 2010 Annual Meeting (2010)
20.
23.
go back to reference van Rosendale, J.: Minimizing inner product data dependencies in conjugate gradient iteration. In: Proceedings of the IEEE international conference on parallel processing. IEEE computer society (1983) van Rosendale, J.: Minimizing inner product data dependencies in conjugate gradient iteration. In: Proceedings of the IEEE international conference on parallel processing. IEEE computer society (1983)
25.
26.
go back to reference Saad, Y., Schultz, M.H.: GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 7, 856–869 (1986)MathSciNetCrossRefMATH Saad, Y., Schultz, M.H.: GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 7, 856–869 (1986)MathSciNetCrossRefMATH
27.
go back to reference Saad, Y., Sosonkina, M.: pARMS: a package for the parallel iterative solution of general large sparse linear systems user’s guide. Tech. Rep. UMSI2004-8, Minnesota Supercomputer Institute, University of Minnesota (2004) Saad, Y., Sosonkina, M.: pARMS: a package for the parallel iterative solution of general large sparse linear systems user’s guide. Tech. Rep. UMSI2004-8, Minnesota Supercomputer Institute, University of Minnesota (2004)
28.
go back to reference Shalf, J., Dosanjh, S., Morrison, J.: Exascale computing technology challenges. In: Palma, J.M.L.M., et al. (eds.) VECPAR 2010, LNCS 6449, pp. 1–25 (2010) Shalf, J., Dosanjh, S., Morrison, J.: Exascale computing technology challenges. In: Palma, J.M.L.M., et al. (eds.) VECPAR 2010, LNCS 6449, pp. 1–25 (2010)
29.
go back to reference Simoncini, V., Szyld, D.: Flexible inner-outer Krylov subspace methods. SIAM J. Numer. Anal. 40(6), 2219–2239 (2003) Simoncini, V., Szyld, D.: Flexible inner-outer Krylov subspace methods. SIAM J. Numer. Anal. 40(6), 2219–2239 (2003)
30.
go back to reference Simoncini, V., Szyld, D.B.: Theory of inexact Krylov subspace methods and applications to scientific computing. SIAM J. Sci. Comput. 25(2), 454–477 (2003)MathSciNetCrossRefMATH Simoncini, V., Szyld, D.B.: Theory of inexact Krylov subspace methods and applications to scientific computing. SIAM J. Sci. Comput. 25(2), 454–477 (2003)MathSciNetCrossRefMATH
31.
go back to reference Sleijpen, G.L., van Gijzen, M.B.: Exploiting BiCGstab(\(\ell \)) strategies to induce dimension reduction. SIAM J. Sci. Comput. 32(5), 2687–2709 (2010)MathSciNetCrossRefMATH Sleijpen, G.L., van Gijzen, M.B.: Exploiting BiCGstab(\(\ell \)) strategies to induce dimension reduction. SIAM J. Sci. Comput. 32(5), 2687–2709 (2010)MathSciNetCrossRefMATH
32.
go back to reference Sleijpen, G.L., Sonneveld, P., van Gijzen, M.B.: Bi-CGSTAB as an induced dimension reduction method. Appl. Numer. Math. 60, 1100–1114 (2010)MathSciNetCrossRefMATH Sleijpen, G.L., Sonneveld, P., van Gijzen, M.B.: Bi-CGSTAB as an induced dimension reduction method. Appl. Numer. Math. 60, 1100–1114 (2010)MathSciNetCrossRefMATH
33.
go back to reference Sonneveld, P., van Gijzen, M.B.: IDR(s): a family of simple and fast algorithms for solving large nonsymmetric systems of linear equations. SIAM J. Sci. Comput. 31(2), 1035–1062 (2008)MathSciNetCrossRefMATH Sonneveld, P., van Gijzen, M.B.: IDR(s): a family of simple and fast algorithms for solving large nonsymmetric systems of linear equations. SIAM J. Sci. Comput. 31(2), 1035–1062 (2008)MathSciNetCrossRefMATH
34.
go back to reference Sturler, E.D., van der Vorst, H.A.: Reducing the effect of global communication in GMRES(m) and CG on parallel distributed memory computers. Appl. Numer. Math. 18, 441–459 (1995)CrossRefMATH Sturler, E.D., van der Vorst, H.A.: Reducing the effect of global communication in GMRES(m) and CG on parallel distributed memory computers. Appl. Numer. Math. 18, 441–459 (1995)CrossRefMATH
35.
go back to reference Szyld, D.B., Vogel, J.A.: FQMR: a flexible quasi-minimal residual method with inexact preconditioning. SIAM J. Sci. Comput. 23(2), 363–380 (2001)MathSciNetCrossRefMATH Szyld, D.B., Vogel, J.A.: FQMR: a flexible quasi-minimal residual method with inexact preconditioning. SIAM J. Sci. Comput. 23(2), 363–380 (2001)MathSciNetCrossRefMATH
36.
go back to reference van der Vorst, H.: BiCGSTAB: a fast and smoothly converging variant of BiCG for the solution of nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 13, 631–644 (1992)CrossRefMATH van der Vorst, H.: BiCGSTAB: a fast and smoothly converging variant of BiCG for the solution of nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 13, 631–644 (1992)CrossRefMATH
37.
38.
go back to reference van Gijzen, M.B., Sleijpen, G.L., Zemke, J.P.M.: Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems. Tech. Rep. 11–06, Delft University of Technology (2011) van Gijzen, M.B., Sleijpen, G.L., Zemke, J.P.M.: Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems. Tech. Rep. 11–06, Delft University of Technology (2011)
39.
go back to reference Vogel, J.A.: Flexible BiCG and flexible Bi-CGSTAB for nonsymmetric linear systems. Appl. Math. Comput. 188(1), 226–233 (2007)MathSciNetMATH Vogel, J.A.: Flexible BiCG and flexible Bi-CGSTAB for nonsymmetric linear systems. Appl. Math. Comput. 188(1), 226–233 (2007)MathSciNetMATH
40.
go back to reference Vuduc, R.: Quantitative performance modeling of scientific computations and creating locality in numerical algorithms. Ph.D. thesis, Massachusetts Institute of Technology (1995) Vuduc, R.: Quantitative performance modeling of scientific computations and creating locality in numerical algorithms. Ph.D. thesis, Massachusetts Institute of Technology (1995)
41.
go back to reference Yang, L.T., Brent, R.: The improved BiCGStab method for large and sparse unsymmetric linear systems on parallel distributed memory architectures. In: Proceedings of the Fifth international conference on algorithms and architectures for parallel processing. IEEE (2002) Yang, L.T., Brent, R.: The improved BiCGStab method for large and sparse unsymmetric linear systems on parallel distributed memory architectures. In: Proceedings of the Fifth international conference on algorithms and architectures for parallel processing. IEEE (2002)
Metadata
Title
Analysis and Practical Use of Flexible BiCGStab
Authors
Jie Chen
Lois C. McInnes
Hong Zhang
Publication date
11-01-2016
Publisher
Springer US
Published in
Journal of Scientific Computing / Issue 2/2016
Print ISSN: 0885-7474
Electronic ISSN: 1573-7691
DOI
https://doi.org/10.1007/s10915-015-0159-4

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