Skip to main content
Log in

Massively parallel methods for semiconductor device modelling

Massiv parallele Verfahren zur Halbleitermodellierung

  • Published:
Computing Aims and scope Submit manuscript

Abstract

In this paper we describe, analyse and implement a parallel iterative method for the solution of the steady-state drift diffusion equations governing the behaviour of a semiconductor device in two space dimensions. The unknowns in our model are the electrostatic potential and the electron and hole quasi-Fermi potentials. Our discretisation consists of a finite element method with mass lumping for the electrostatic potential equation and a hybrid finite element with local current conservation properties for the continuity equations. A version of Gummel's decoupling algorithm which only requires the solution of positive definite symmetric linear systems is used to solve the resulting nonlinear equations. We show that this method has an overall rate of convergence which only degrades logarithmically as the mesh is refined. Indeed the (inner) nonlinear solves of the electrostatic potential equation converge quadratically, with a mesh independent asymptotic constant. We also describe an implementation on a MasPar MP-1 data parallel machine, where the required linear systems are solved by the preconditioned conjugate gradient method. Domain decomposition methods are used to parallelise the required matrix-vector multiplications and to build preconditioners for these very poorly-conditioned systems. Our preconditioned linear solves also have a rate of convergence which degrades logarithmically as the grid is refined relative to subdomain size, and their performance is resilient to the severe layers which arise in the coefficients of the underlying elliptic operators. Parallel experiments are given.

Zusammenfassung

Diese Arbeit enthält die Beschreibung, Analyse und Implementierung eines parallelen iterativen Verfahrens zur Lösung der stationären Drift-Diffusions-Gleichung für ein zweidimensionales Halbleitermodell. Die Unbekannten unseres Modells sind das elektrostatische Potential und die Quasi-Fermi-Potentiale der Elektronen und Löcher. Unsere Diskretisierung verwendet die Finite-Element-Methode mit ‘mass limping’ für das elektrostatische Potential und hybride Elemente mit lokaler Stromerhaltung für die Kontinuitätsgleichung. Zur Lösung der entsprechenden nichtlinearen Gleichungen wird eine Version des Gummel-Algorithmus verwendet, der lediglich die Lösung positiv definiter, symmetrischer linearer Gleichungssysteme erfordert. Wir zeigen, daß diese Methode eine Konvergenzrate besitzt, die nur logarithmisch von der Schrittweite abhängt. Die (inneren) nichtlinearen Löser der elektrostatischen Potentialgleichung konvergieren gitterunabhängig quadratisch. Wir beschreiben auch eine Implementierung auf einem MasPar MP-1-Parallelrechner, wobei die auftretenden linearen Systeme mit einem vorkonditionierten cg-Verfahren approximiert werden. Gebietszerlegungsmethoden werden eingesetzt, um die notwendige Matrix-Vektor-Multiplikation zu parallelisieren und Vorkonditionierer dieser schlechtkonditionierten Systeme zu erstellen. Die vorkonditionierten linearen Löser haben ebenfalls eine Konvergenzrate, die logarithmisch vom Verhältnis Teilgebietsgröße zu Schrittweite abhängt und welche robust ist bezüglich stark variierenden Koeffizientenfunktionen des zugrundeliegenden elliptischen Operators. Experimente auf einem Parallelrechner werden diskutiert.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Babuska, I., Osborne, J. E.: Generalised finite element methods: their performance and their relation to mixed methods. SIAM. J. Numer. Anal.20, 510–536 (1983).

    Google Scholar 

  2. Bank, R. E.: PLTMG: A software package for solving elliptic partial differential equations. Philadelphia: SIAM 1990.

    Google Scholar 

  3. Bank, R. E., Coughran, W. M., Driscoll, M. A., Smith, R. K., Fichtner, W.: Iterative methods in semiconductor device simulation. Comput. Phys. Commun.53, 201–212 (1989).

    Google Scholar 

  4. Bank, R. E., Rose, D. J., Fichtner, W. F.: Numerical methods for semiconductor device simulation. SIAM J. Sci. Stat. Comp.4, 416–435 (1983).

    Google Scholar 

  5. Bjørstad, P. E., Widlund, O. B.: Iterative methods for the solution of elliptic problems on regions partitioned into substructures. SIAM J. Numer. Anal.23, 1097–1120 (1986).

    Google Scholar 

  6. Bramble, J. H., Pasciak, J. E., Schatz, A. H.: The construction of preconditioners for elliptic problems by substructuring. Math Comp.47, 103–134 (1986).

    Google Scholar 

  7. Brezzi, F., Marini, L. D., Pietra. P.: Numerical simulation of semiconductor devices. Comp. Meth. Appl. Mech. Eng.75, 493–514 (1989).

    Google Scholar 

  8. Ciarlet, P. G.: The finite element method for elliptic problems. Amsterdam: North-Holland 1978.

    Google Scholar 

  9. Coomer., R. K.: Parallel iterative methods in semiconductor device modelling. PhD thesis, School of Mathematical Sciences, University of Bath, 1994.

  10. Coomer, R. K., Graham, I. G.: Domain decomposition methods for device modelling. In: Keyes, D. E., Xu, J. (eds.) Domain decomposition techniques in science and engineering. Providence American Mathematical Society, 1994.

    Google Scholar 

  11. De Zeeuw, P. M.: Nonlinear multigrid applied to a 1D stationary semiconductor model. SIAM J. Sci. Stat. Comp.13, 512–530 (1992).

    Google Scholar 

  12. Dryja, M., Widlund, O. B.: Some domain decomposition algorithms for elliptic problems. In: Hayes, L., Kincaid, D. (eds.) Iterative methods for large linear systems. Orlando: Academic Press 1989.

    Google Scholar 

  13. Dryja, M., Widlund, O. B.: Multilevel additive methods for elliptic finite element problems. In: Hackbusch, W. (ed.) Parallel algorithms for PDEs. Braunschweig: Vieweg 1991.

    Google Scholar 

  14. Gummel, H. K.: A self-consistent iterative scheme for one-dimensional steady state transistor calculations. IEEE Trans. Electronic Dev.ED-11, 455–465 (1964).

    Google Scholar 

  15. Jerome, J. W.: Consistency of semiconductor modeling: an existence/stability analysis for the stationary Van Roosbroeck system. SIAM. J. Appl. Math.45, 565–590 (1985).

    Google Scholar 

  16. Jerome, J. W., Kerkhoven, T.: A finite element approximation theory for the drift diffusion semiconductor model. SIAM J. Numer. Anal.28, 403–422 (1991).

    Google Scholar 

  17. Johnson, C.: Numerical solutions of partial differential equations by the finite element method. Cambridge: Cambridge University Press 1987.

    Google Scholar 

  18. Kerkhoven, T.: Coupled and decoupled algorithms for semiconductor simulation. PhD thesis, Department of Computer Science, Yale University, 1985 (Yale Research Report YALEU/DCS/RR-429).

  19. Kerkhoven, T.: A proof of convergence of Gummel's algorithm for realistic device geometries. SIAM J. Numer. Anal.23, 1121–1136 (1986).

    Google Scholar 

  20. Kerkhoven, T.: On the effectiveness of Gummel's method. SIAM J. Sci. Stat. Comput.9, 48–60 (1988).

    Google Scholar 

  21. Mandel, J.: Hybrid domain decomposition with unstructured subdomains. Preprint, 1993.

  22. Markowich, P. A.: The stationary semiconductor device equations. Wien-New York: Springer 1986.

    Google Scholar 

  23. Markowich, P. A., Ringhofer, C. A., Schmeiser, C.: Semiconductor equations. Wien-New York: Springer 1990.

    Google Scholar 

  24. Markowich, P. A., Zlámal, M. A.: Inverse-average-type finite element discretizations of selfadjoint second-order elliptic problems. Math. Comput.51, 431–449 (1988).

    Google Scholar 

  25. MasPar Computer corporation, Sunnyvale, California, 1990. MasPar system overview.

  26. Ortega, J. M., Rheinboldt, W. C.: Iterative solution of nonlinear equations in several variables. New York: Academic Press 1970.

    Google Scholar 

  27. Patankar, S. V.: Numerical heat transfer and fluid flow. New York: McGraw-Hill 1980.

    Google Scholar 

  28. Polak, S. J., Den Heijer, C., Schilders, W. H. A., Markowich, P.: Semiconductor device modelling from the numerical point of view. Int. J. Numer. Meth. Eng.24, 763–838 (1987).

    Google Scholar 

  29. Potra, F. A.: Newton-like methods with monotone convergence for solving nonlinear operator equations. Nonlinear Anal. Theory Meth. Appl.11, 697–717 (1987).

    Google Scholar 

  30. Scharfetter, D. L., Gummel, H. K.: Large-signal analysis of a silicon Read diode oscillator. IEEE Trans. Electron Dev.ED-16, 64–77 (1991).

    Google Scholar 

  31. Smith, B. F.: A domain decomposition algorithm for elliptic problems in three dimensions. Numer. Math.60, 219–234 (1991).

    Google Scholar 

  32. Smith, B. F.: An optimal domain decomposition preconditioner for the finite element solution of linear elasticity problems. SIAM. J. Sci. Stat. Comput.13, 364–378 (1992).

    Google Scholar 

  33. Smith, B. F., Widlund, O. B.: A domain decomposition algorithm using a hierarchical basis. SIAM J. Sci. Stat. Comp.11, 1212–1220 (1990).

    Google Scholar 

  34. Wang, Z.-Y., Wu, K.-C., Dutton, R. W.: An approach to construct pre conditioning matrices for block iteration of linear equations. IEEE Trans. CAD11, 1334–1343 (1992).

    Google Scholar 

  35. Wu, K.-C., Lucas, Z.-Y., Dutton, R. W.: New approaches in a 3D one-carrier device solver. IEEE Trans. CAD8, 528–537 (1989).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Coomer, R.K., Graham, I.G. Massively parallel methods for semiconductor device modelling. Computing 56, 1–27 (1996). https://doi.org/10.1007/BF02238289

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02238289

AMS Subject Classifications

Key words

Navigation