A novel parallel adaptive Monte Carlo method for nonlinear Poisson equation in semiconductor devices

Yi-Ming Li*, Hsiao Mei Lu, Ting Wei Tang, S. M. Sze

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

30 Scopus citations

Abstract

We present a parallel adaptive Monte Carlo (MC) algorithm for the numerical solution of the nonlinear Poisson equation in semiconductor devices. Based on a fixed random walk MC method, 1-irregular unstructured mesh technique, monotone iterative method, a posterior error estimation method, and dynamic domain decomposition algorithm, this approach is developed and successfully implemented on a 16-processors (16-PCs) Linux-cluster with message-passing interface (MPI) library. To solve the nonlinear problem with MC method, monotone iterative method is applied in each adaptive loop to obtain the final convergent solution. This approach fully exploits the inherent parallelism of the monotone iterative as well as MC methods. Numerical results for p-n diode and MOSFET devices are demonstrated to show the robustness of the method. Furthermore, achieved parallel speedup and related parallel performances are also reported in this work.

Original languageEnglish
Pages (from-to)413-420
Number of pages8
JournalMathematics and Computers in Simulation
Volume62
Issue number3-6
DOIs
StatePublished - 3 Mar 2003
EventMCM 2001 - Salzburg, Austria
Duration: 10 Sep 200114 Sep 2001

Keywords

  • Device simulation
  • Monte Carlo method
  • Nonlinear Poisson equation
  • Unstructured mesh

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