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Monte Carlo Simulations on SIMD Computer Architectures

Published online by Cambridge University Press:  26 February 2011

C. P. Burmester,
L. T. Wille and
R. Gronsky
C. P. Burmester
Affiliation:
Department of Materials Science and Mineral Engineering, University of California at Berkeley, CA: and Materials Science Division, Lawrence Berkeley Laboratory, Berkeley, CA 94720.
L. T. Wille
Affiliation:
Department of Physics, Florida Atlantic University, Boca Raton, FL 33431.
R. Gronsky
Affiliation:
Department of Materials Science and Mineral Engineering, University of California at Berkeley, CA: and Materials Science Division, Lawrence Berkeley Laboratory, Berkeley, CA 94720.
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Abstract

Algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SIMD) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest. and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carlo updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures.

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Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 278: Symposium W – Computational Methods in Materials Science , 1992, 3
Copyright
Copyright © Materials Research Society 1992

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