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Parallel simulation of electron-solid interactions for electron microscopy modeling

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Abstract

A parallel implementation of a Monte Carlo algorithm for modeling the scattering of electrons in solids and the resulting X-ray production is described. Two important issues for accurate and fast parallel simulation are discussed-random number generation and load-balancing. Timing results for the parallel simulation are given which show even modest-sized parallel machines can be competitive with conventional vector supercomputers for Monte Carlo trajectory simulations. Examples of parallel calculations performed to analyze specimen composition data and to characterize electron microscope performance are briefly highlighted.

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References

  • Bailey, D. 1991. The NAS parallel benchmarks. NASA Ames tech. rept., Moffett Field, Calif.

  • Bowman, K., and Robinson, M. 1987. Studies of random number generators for parallel processing. In Hypercube '87 Conf. (Oak Ridge, Tenn.), p. 445.

  • Fox, G., et al. 1988. Solving problems on concurrent processors. Prentice-Hall, Englewood Cliffs, N.J., p. 210.

    Google Scholar 

  • Frederickson, P., Hiromoto, R., and Larson, J. 1987. A parallel Monte Carlo transport algorithm using a pseudo-random tree to guarantee reproducibility. Parallel Computing, 4:281.

    Google Scholar 

  • Goldstein, J.I., Costley, J.L., Lorimar, G.W., and Reed, S.F.B. 1977. Quantitative X-ray analysis in the electron microscope. In Scanning Electron Microscopy, vol. 1 (O. Jahari. ed.), IITRI, Chicago, p. 315.

    Google Scholar 

  • Gustafson, J.L., Benner, R.E., Sears, M.P., and Sullivan, T.D. 1989. A radar simulation program for a 1024-processor hypercube. In Proc., Supercomputing '89 (Reno, Nev., Nov. 13–17), ACM SIGARCH and IEEE Comp. Soc., p. 96.

  • James, F. 1990. A review of pseudorandom number generators. Comp. Phys. Comm., 60:329.

    Google Scholar 

  • Lyman, C.E. 1986. Microanalysis limits on the use of energy-dispersive X-ray spectroscopy in the analytical electron microscope. In Microbeam Analysis—1986 (A.D. Romig Jr., and W.F. Chambers, eds.), San Francisco Press, p. 434.

  • Martin, W.R. 1988. Particle transport Monte Carlo on shared-memory and distributed-memory parallel processors. In Proc., Supercomputing '88 (Orlando, Fla., Nov. 14–18), IEEE Comp. Soc. and ACM SIGARCH, p. 348.

  • Martin, W.R. 1989. Successful vectorization-Reactor physics Monte Carlo code. Comp. Phys. Comm., 57:68.

    Google Scholar 

  • Michael, J.R., Romig, A.D. Jr., and Goldstein, J.I. 1991. Thin film X-ray quantitation: New insights with the aid of Monte Carlo calculations. In Proc., Electron Microscopy Soc. of Am. (EMSA) (G.W. Bailey, and E.L. Hall, eds.), San Francisco Press, p. 718.

  • Michael, J.R., Williams, D.B., Klein, C.F., and Ayer, R. 1990. The measurement and calculation of the X-ray spatial resolution obtained in the analytical electron microscope. J. Microscopy, 160:41.

    Google Scholar 

  • Miura, K. 1987. EGS4V: Vectorization of the Monte Carlo cascade shower simulation code EGS4. Comp. Phys. Comm., 45:127.

    Google Scholar 

  • Miura, K., and Babb, R.G., II. 1988. Tradeoffs in granularity and parallelization for a Monte Carlo shower simulation code. Parallel Computing, 8:91.

    Google Scholar 

  • Newbury, D.E. 1986. Electron beam-specimen interactions in the analytical electron microscope. In Principles of Analytical Electron Microscopy (D.C. Joy, A.D. Romig Jr., J.I. Goldstein, eds.), Plenum Press, New York, p1.

    Google Scholar 

  • Newbury, D.E., and Myklebust, R.L. 1979. Monte Carlo electron trajectory simulation of beam spreading in thin foil targets. Ultramicros copy, 3:391.

    Google Scholar 

  • Newbury, D.E., and Myklebust, R.L. 1981. A Monte Carlo electron trajectory simulation for analytical electron microscopy. In Analytical Electron Microscopy—1981 (R.H. Geiss, ed.), San Francisco Press, p. 91.

  • Park, S.K., and Miller, K.W. 1988. Random number generators: Good ones are hard to find. CACM, 31:1192.

    Google Scholar 

  • Percus, O.E., and Kalos, M.H. 1989. Random number generators for MIMD parallel processors. J. Parallel and Distr. Comp., 6:477.

    Google Scholar 

  • Romig, A.D. Jr., Michael, J.R., and Goldstein, J.I. 1991. X-ray spatial resolution of intermediate voltages: An assessment by massively parallel Monte Carlo electron trajectory simulation. In Microbeam Analysis—1991, (D.G. Howitt, ed.), San Francisco Press, p. 119.

  • Romig, A.D. Jr., Plimpton, S.J., Michael, J.R., Myklebust, R.L., and Newbury, D.E. 1990. Application of parallel computing to the Monte Carlo simulation of electron scattering in solids: A rapid method for profile deconvolution. In Microbeam Analysis—1990, (J.R. Michael and P. Imgram, eds.), San Francis Press, p. 275.

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Plimpton, S.J., Michael, J.R. & Romig, A.D. Parallel simulation of electron-solid interactions for electron microscopy modeling. J Supercomput 6, 139–151 (1992). https://doi.org/10.1007/BF00129775

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