Analysis and Practical Use of Flexible BiCGStab

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(104)–$$O(10^5)$$O(105) processor cores.

[1]  Gerard L. G. Sleijpen,et al.  Exploiting BiCGstab(ℓ) Strategies to Induce Dimension Reduction , 2010, SIAM J. Sci. Comput..

[2]  Barry Smith,et al.  Engineering PFLOTRAN for Scalable Performance on Cray XT and IBM BlueGene Architectures , 2010 .

[3]  Matthew G. Knepley,et al.  Composable Linear Solvers for Multiphysics , 2012, 2012 11th International Symposium on Parallel and Distributed Computing.

[4]  Gerard L. G. Sleijpen,et al.  Inexact Krylov Subspace Methods for Linear Systems , 2004, SIAM J. Matrix Anal. Appl..

[5]  James Demmel,et al.  Minimizing communication in sparse matrix solvers , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[6]  Gene H. Golub,et al.  Inexact Preconditioned Conjugate Gradient Method with Inner-Outer Iteration , 1999, SIAM J. Sci. Comput..

[7]  Cornelis Vuik,et al.  GMRESR: a family of nested GMRES methods , 1994, Numer. Linear Algebra Appl..

[8]  Yvan Notay Flexible Conjugate Gradients , 2000, SIAM J. Sci. Comput..

[9]  Hong Zhang,et al.  Hierarchical Krylov and nested Krylov methods for extreme-scale computing , 2014, Parallel Comput..

[10]  Gerard L. G. Sleijpen,et al.  Bi-CGSTAB as an induced dimension reduction method , 2010 .

[11]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[12]  J. Vanrosendale,et al.  Minimizing inner product data dependencies in conjugate gradient iteration , 1983 .

[13]  Valérie Frayssé,et al.  Inexact Matrix-Vector Products in Krylov Methods for Solving Linear Systems: A Relaxation Strategy , 2005, SIAM J. Matrix Anal. Appl..

[14]  Kurt B. Ferreira,et al.  Fault-tolerant linear solvers via selective reliability , 2012, ArXiv.

[15]  H. V. D. Vorst,et al.  Reducing the effect of global communication in GMRES( m ) and CG on parallel distributed memory computers , 1995 .

[16]  John Shalf,et al.  Exascale Computing Technology Challenges , 2010, VECPAR.

[17]  Daniel B. Szyld,et al.  FQMR: A Flexible Quasi-Minimal Residual Method with Inexact Preconditioning , 2001, SIAM J. Sci. Comput..

[18]  M. Fortin,et al.  An efficient hierarchical preconditioner for quadratic discretizations of finite element problems , 2011, Numer. Linear Algebra Appl..

[19]  Anthony T. Chronopoulos,et al.  s-step iterative methods for symmetric linear systems , 1989 .

[20]  Martin B. van Gijzen,et al.  IDR(s): A Family of Simple and Fast Algorithms for Solving Large Nonsymmetric Systems of Linear Equations , 2008, SIAM J. Sci. Comput..

[21]  Gene H. Golub,et al.  Inner and Outer Iterations for the Chebyshev Algorithm , 1998 .

[22]  Sivan Toledo,et al.  Quantitative performance modeling of scientific computations and creating locality in numerical algorithms , 1995 .

[23]  Wim Vanroose,et al.  Hiding Global Communication Latency in the GMRES Algorithm on Massively Parallel Machines , 2013, SIAM J. Sci. Comput..

[24]  L.T. Yang,et al.  The improved BiCGStab method for large and sparse unsymmetric linear systems on parallel distributed memory architectures , 2002, Fifth International Conference on Algorithms and Architectures for Parallel Processing, 2002. Proceedings..

[25]  O. Axelsson,et al.  A black box generalized conjugate gradient solver with inner iterations and variable-step preconditioning , 1991 .

[26]  Matthew G. Knepley,et al.  PETSc Users Manual: Revision 3.11 , 2019 .

[27]  R. Fletcher Conjugate gradient methods for indefinite systems , 1976 .

[28]  Valeria Simoncini,et al.  Theory of Inexact Krylov Subspace Methods and Applications to Scientific Computing , 2003, SIAM J. Sci. Comput..

[29]  Valeria Simoncini,et al.  Flexible Inner-Outer Krylov Subspace Methods , 2002, SIAM J. Numer. Anal..

[30]  Masha Sosonkina,et al.  pARMS : A Package for the Parallel Iterative Solution of General Large Sparse Linear System ∗ User ’ s Guide , 2006 .

[31]  Emil M. Constantinescu,et al.  Multiphysics simulations , 2013, HiPC 2013.

[32]  Yousef Saad,et al.  A Flexible Inner-Outer Preconditioned GMRES Algorithm , 1993, SIAM J. Sci. Comput..

[33]  Gerard L. G. Sleijpen,et al.  Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems , 2011 .

[34]  Henk A. van der Vorst,et al.  Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems , 1992, SIAM J. Sci. Comput..

[35]  William Gropp,et al.  Efficient Management of Parallelism in Object-Oriented Numerical Software Libraries , 1997, SciTools.

[36]  Y. Saad,et al.  GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems , 1986 .

[37]  Judith A. Vogel,et al.  Flexible BiCG and flexible Bi-CGSTAB for nonsymmetric linear systems , 2007, Appl. Math. Comput..