PMC-3D: A Parallel Three-Dimensional Monte Carlo Semiconductor Device Simulator

Udaya A. Ranawake; Carl Huster; Patrick M. Lenders; Stephen M. Goodnick

doi:10.1109/43.285244

PMC-3D: A Parallel Three-Dimensional Monte Carlo Semiconductor Device Simulator

Udaya A. Ranawake, Carl Huster, Patrick M. Lenders, Stephen M. Goodnick

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

We present PMC-3D, a parallel three-dimensional (3-D) Monte Carlo device simulator for multiprocessors. The parallel algorithm is an extension of the standard Monte Carlo device simulation model in 3-D, in which the particle dynamics generated from the stochastic Monte Carlo method are solved simultaneously with Poisson's equation on a 3-D mesh using finite differences. Due to the large computational requirements of 3-D device simulation, it is necessary to parallelize both the Poisson solver and the Monte Carlo simulation phase of the device simulator. The parallel algorithms were implemented on a 1024-node distributed memory nCUBE multicomputer and a 4-node shared memory Ardent multiprocessor. We validate the accuracy of our implementations by generating the static characteristics of a MESFET and present test results on the fixed and scaled speedups obtained on the two types of parallel computers. Improvements in performance are observed utilizing dynamic load balancing for the distributed memory case.

Original language	English (US)
Pages (from-to)	712-724
Number of pages	13
Journal	IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume	13
Issue number	6
DOIs	https://doi.org/10.1109/43.285244
State	Published - Jun 1994
Externally published	Yes

ASJC Scopus subject areas

Software
Computer Graphics and Computer-Aided Design
Electrical and Electronic Engineering

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10.1109/43.285244

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title = "PMC-3D: A Parallel Three-Dimensional Monte Carlo Semiconductor Device Simulator",

abstract = "We present PMC-3D, a parallel three-dimensional (3-D) Monte Carlo device simulator for multiprocessors. The parallel algorithm is an extension of the standard Monte Carlo device simulation model in 3-D, in which the particle dynamics generated from the stochastic Monte Carlo method are solved simultaneously with Poisson's equation on a 3-D mesh using finite differences. Due to the large computational requirements of 3-D device simulation, it is necessary to parallelize both the Poisson solver and the Monte Carlo simulation phase of the device simulator. The parallel algorithms were implemented on a 1024-node distributed memory nCUBE multicomputer and a 4-node shared memory Ardent multiprocessor. We validate the accuracy of our implementations by generating the static characteristics of a MESFET and present test results on the fixed and scaled speedups obtained on the two types of parallel computers. Improvements in performance are observed utilizing dynamic load balancing for the distributed memory case.",

author = "Ranawake, {Udaya A.} and Carl Huster and Lenders, {Patrick M.} and Goodnick, {Stephen M.}",

note = "Funding Information: Manuscript received December 21, 1992; revised November 22, 199. This work was funded by the National Science Foundation grant number ECS-8821 107. This paper was recommended by Associate Editor J. White. U. Ranawake is with Hughes STX Corp., Lanham, MA USA. C. Huster is at the School of Electrical Engineering, F{\textquoteright}urdue University, West Lafayette, IN USA. P. Lenders is with the Department of Computer Science, the University of New England, Australia. S. Goodnick is at the Department of Electrical and Computer Engineering, Oregon State University, Corvallis, OR 9733 I USA. IEEE Log Number 9215137. Funding Information: The authors would like to thank the staff members of Sandia National Lab andthe San Diego supercomputer center for providing access to their nCUBE parallel computers. The authors also acknowledge the support of the National Center for Computational Electronics (NCCE) and the National Supercomputer Center for Supercomputing Applications (NCSA) in Urbana, Illinois.",

year = "1994",

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doi = "10.1109/43.285244",

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AU - Goodnick, Stephen M.

N1 - Funding Information: Manuscript received December 21, 1992; revised November 22, 199. This work was funded by the National Science Foundation grant number ECS-8821 107. This paper was recommended by Associate Editor J. White. U. Ranawake is with Hughes STX Corp., Lanham, MA USA. C. Huster is at the School of Electrical Engineering, F’urdue University, West Lafayette, IN USA. P. Lenders is with the Department of Computer Science, the University of New England, Australia. S. Goodnick is at the Department of Electrical and Computer Engineering, Oregon State University, Corvallis, OR 9733 I USA. IEEE Log Number 9215137. Funding Information: The authors would like to thank the staff members of Sandia National Lab andthe San Diego supercomputer center for providing access to their nCUBE parallel computers. The authors also acknowledge the support of the National Center for Computational Electronics (NCCE) and the National Supercomputer Center for Supercomputing Applications (NCSA) in Urbana, Illinois.

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N2 - We present PMC-3D, a parallel three-dimensional (3-D) Monte Carlo device simulator for multiprocessors. The parallel algorithm is an extension of the standard Monte Carlo device simulation model in 3-D, in which the particle dynamics generated from the stochastic Monte Carlo method are solved simultaneously with Poisson's equation on a 3-D mesh using finite differences. Due to the large computational requirements of 3-D device simulation, it is necessary to parallelize both the Poisson solver and the Monte Carlo simulation phase of the device simulator. The parallel algorithms were implemented on a 1024-node distributed memory nCUBE multicomputer and a 4-node shared memory Ardent multiprocessor. We validate the accuracy of our implementations by generating the static characteristics of a MESFET and present test results on the fixed and scaled speedups obtained on the two types of parallel computers. Improvements in performance are observed utilizing dynamic load balancing for the distributed memory case.

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PMC-3D: A Parallel Three-Dimensional Monte Carlo Semiconductor Device Simulator

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