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Application of Parallel Ensemble Monte Carlo Technique in Charge Dynamics Simulation

Othman A.P., and Umar R., and Gopir, G., (2008) Application of Parallel Ensemble Monte Carlo Technique in Charge Dynamics Simulation. Sains Malaysiana , 37 (1). pp. 89-93. ISSN 01266039

Full text not available from this repository.

Official URL: http://pkukmweb.ukm.my/~jsm/pdf_files/SM-PDF-37(1)March2008/12.%20A.P.pdf

Affiliations

Universiti Kebangsaan Malaysia. School of Applied Physics
Universiti Kebangsaan Malaysia. School of Applied Physics
Universiti Kebangsaan Malaysia. School of Applied Physics

Abstract

In the past, simulating charge dynamics in solid state devices, such as current mobility, transient current drift velocities are done on mainframe systems or on high performance computing facilities. This is due to the fact that, such simulations are costly in terms of computational requirements when implemented on a single processor-based personal computers (PCs). When simulating charge dynamics, large ensembles of particles are usually preferred, such as exceeding 40000 particles, to ensure a numerically sound result. When implementing this type of simulation on a single processor PCs using the conventional ensemble or single particle Monte Carlo method, the computational time is very long even on the fast 2.0 MHz PCs. Lately, a more efficient, easily made available tools and cost effective solution to this problem is the application of an array of PCs employed in a parallel application. This is done using a computer cluster network in a master-slave model. In this paper we report the development of a LINUX cluster for the purpose of implementing parallel ensemble Monte Carlo modelling for solid states device. We have proposed the use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation. Some results of the development are also presented in this paper.

(Di masa yang lepas, simulasi dinamik cas bagi peranti pepejal seperti mobiliti arus dan halaju hanyut arus fana dijalankan pada sistem kerangka utama atau pada sistem komputer berprestasi tinggi. Perkara ini berlaku kerana simulasi seperti ini sangatlah membebankan jika dijalankan pada komputer peribadi (PC) yang berasaskan pemprosesan tunggal. Bagi tujuan simulasi dinamik cas, himpunan zarah yang banyak, melebihi 40000 zarah biasanya diperlukan bagi menghasilkan keputusan yang memuaskan. Jika simulasi yang melibatkan zarah sebanyak ini dijalankan pada PC berpemprosesan tunggal dengan kaedah Monte Carlo ensemble atau Monte Carlo zarah tunggal yang lazim, masa komputasi yang diperlukan adalah terlalu lama, walaupun jika kita menggunakan PC dengan pemprosesan 2.0 MHz. Akhir-akhir ini, kaedah simulasi yang lebih cekap, mudah dibangunkan dan menjimatkan telah wujud, ia itu dengan penggunaan rangkaian PC yang dijalankan dalam aplikasi sejajar. Kaedah ini dilakukan dengan pembangunan jaringan kluster dalam model pelayan-klien. Pada kertas kerja ini kami melaporkan pembangunan satu rangkaian kluster LINUX bagi mensimulasikan pemodelan peranti keadaan pepejal dengan kaedah Monte Carlo Ensembel secara sejajar. Kami telah mencadangkan penggunaan piawai Parallel Virtual Machine (PVM) bagi menjalankan algorithma yang dibangunkan. Kami juga menyertakan hasil simulasi yang jalankan pada kluster LINUX yang telah dibangunkan.

Item Type:Journal
Keywords:Monte Carlo; charge dynamics; parallel algorithm; LINUX Cluster
Subjects:Q Science, Computer Science
ID Code:2808

Bookman, C., 2003. LINUX Clustering, Building and Maintaing LINUX Clusters New York.

Ferrenberg, A.M., Landau, D.P., & Wong Y.J., 1992. Monte Carlo simulations: Hidden errors from ‘good’ random number generators. Phys. Rev. Lett. 69: 3382.

Fischetti, M.V. & Laux, S.E., 1988. Monte Carlo Analysis of Electron transport in small semiconductor devices including band structure and space-charge effects. Phys. Rev. B 38 (19): 9721-9727.

Jacoboni, C. & Reggian, L. 1983. The Monte carlo method for solution of charge transport in semiconductors with application to covalent materials Rev. Mod. Phys. 55 (3): 645.

Jacoboni, C. and Lugli, P. 1989. The Monte carlo method for Semiconductor Device Simulation. New York: Springer-Verlag.

Karl Hess, 1991. Monte Carlo Device Simulation: Full Band and Beyond Dordrecht, The Netherlands: Kluwer Academic Publishers Group.

Kurosawa, T. 1966. Monte carlo Simulation of hot electron problems, J. Phys. Soc. Suppl. 21: 527-529.

Rubinstein, R.V. 1981. Simulation and the Monte Carlo Method. New York: John Wiley & Sons,

Vattulainen, I. & Ala-Nissila, T. 1995 Mission impossible: Find a random pseudorandom number generator. Comput. in Phys. 9: 500.

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