Performance Issues for Iterative Solvers in Device Simulation

Due to memory limitations, iterative methods have become the method of choice for large scale semiconductor device simulation. However, it is well known that these methods suffer from reliability problems. The linear systems that appear in numerical simulation of semiconductor devices are notoriously ill conditioned. In order to produce robust algorithms for practical problems, careful attention must be given to many implementation issues. This paper concentrates on strategies for developing robust preconditioners. In addition, effective data structures and convergence check issues are also discussed. These algorithms are compared with a standard direct sparse matrix solver on a variety of problems.

[1]  G. Golub,et al.  Gmres: a Generalized Minimum Residual Algorithm for Solving , 2022 .

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

[3]  L. Dutto The effect of ordering on preconditioned GMRES algorithm, for solving the compressible Navier-Stokes equations , 1993 .

[4]  Robert W. Dutton,et al.  New approaches in a 3-D one-carrier device solver , 1989, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[5]  Bi-cgstab in Semiconductor Modelling , 1990 .

[6]  Roland W. Freund,et al.  A Transpose-Free Quasi-Minimal Residual Algorithm for Non-Hermitian Linear Systems , 1993, SIAM J. Sci. Comput..

[7]  P. Sonneveld CGS, A Fast Lanczos-Type Solver for Nonsymmetric Linear systems , 1989 .

[8]  Wei-Pai Tang,et al.  Ordering Methods for Preconditioned Conjugate Gradient Methods Applied to Unstructured Grid Problems , 1992, SIAM J. Matrix Anal. Appl..

[9]  Wei-Pai Tang,et al.  Weighted graph based ordering techniques for preconditioned conjugate gradient methods , 1995 .

[10]  J. M. Aarden,et al.  Preconditioned CG-type methods for solving the coupled system of fundamental semiconductor equations , 1989 .

[11]  Gernot Heiser,et al.  Three-dimensional numerical semiconductor device simulation: algorithms, architectures, results , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[12]  E. D'Azevedo,et al.  Drop tolerance preconditioning for incompressible viscous flow , 1992 .

[13]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[14]  E. D'Azevedo,et al.  Towards a cost-effective ILU preconditioner with high level fill , 1992 .

[15]  Randolph E. Bank,et al.  Iterative methods in semiconductor device simulation , 1989 .

[16]  W. M. Coughran,et al.  The alternate-block-factorization procedure for systems of partial differential equations , 1989 .

[17]  Vijay Sonnad,et al.  A comparison of direct and preconditioned iterative techniques for sparse, unsymmetric systems of linear equations , 1989 .

[18]  S. Doi,et al.  A Graph-theory approach for analyzing the effects of ordering on ILU preconditionning , 1991 .

[19]  Yvan Notay,et al.  Ordering Methods for Approximate Factorization Preconditioning , 1993 .

[20]  J. Pasciak,et al.  Computer solution of large sparse positive definite systems , 1982 .

[21]  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..

[22]  Robert W. Dutton,et al.  An approach to construct pre-conditioning matrices for block iteration of linear equations , 1992, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[23]  Wei-Pai Tang,et al.  Preconditioned conjugate gradient methods for the incompressible Navier-Stokes equations , 1992 .

[24]  Siegfried Selberherr,et al.  Fast Iterative Solution of Carrier Continuity Equations for Three-Dimensional Device Simulation , 1992, SIAM J. Sci. Comput..

[25]  A. Bruaset A survey of preconditioned iterative methods , 1995 .

[26]  I. Duff,et al.  The effect of ordering on preconditioned conjugate gradients , 1989 .