Geodesic
Effective use of multicore coprocessors in supercomputer stochastic simulation of electron avalanches
Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika, Tome 2 (2013) no. 4, pp. 80-93 Cet article a éte moissonné depuis la source Math-Net.Ru

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Three-dimensional parallel Monte Carlo algorithm for modelling the electron avalanches in gases is developed. Parallel Implementation is made on supercomputers with MPP architecture and on hybrid supercomputers with Intel Xeon Phi coprocessors. The well-working library PARMONC is used to implement parallel computations. The use of the library enables fast calculation of functionals such as the number of particles in avalanche, first Townsend coefficient, drift velocity, etc.
Mots-clés : electron avalanche
Keywords: Monte Carlo method, parallelization, supercomputer. 
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M. A. Marchenko. Effective use of multicore coprocessors in supercomputer stochastic simulation of electron avalanches. Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika, Tome 2 (2013) no. 4, pp. 80-93. http://geodesic.mathdoc.fr/item/VYURV_2013_2_4_a5/

[1] S. M. Ermakov, G. A. Mikhailov, Course of stochastic simulation, Nauka, Moscow, 1976, 320 pp.

[2] A. F. Akkerman, Simulation of trajectories of charged particles in medium, Fundamental and applied mathematics, Energoatomizdat, Moscow, 1991, 200 pp.

[3] G. J. M. Hagelaar, L. C. Pitchford, “Solving the Boltzmann equation to obtain electron transport coefficients and rate coefficients for fluid models”, Plasma Sources Sci. Technol, 14 (2005), 722–733

[4] Ju. D. Korolev, G. A. Mesyatc, Physics if impulse breakdown in gases, Nauka, Moscow, 1991, 224 pp.

[5] G. Z. Lotova, M. A. Marchenko, G. A. Mikhailov, et al., “Parallel realization of Monte Carlo method for modelling of electron avalanches in gases”, Izvestiya vyshyh uchebnyh zavedeniy, 2013

[6] Y. Itikawa, M. Hayashi, A. Ichimura, K. Onda, K. Sakimoto, K. Takayanagi, M. Nakamura, H. Nishimura, T. Takayanagi, “Sections for Collisions of Electrons and Photons with Nitrogen Molecules”, J. Phys. Chem. Ref. Data, 15:3 (1986), 985–1010

[7] A. Okhrimovskyy, A. Bogaerts, R. Gijbels, “Electron anisotropic scattering in gases: A formula for Monte Carlo simulations”, Phys. Rev. E., 65:037402 (1986), 1–4

[8] W. Sun, M. A. Morrison, W. A. Isaacs, W. K. Trail, D. T. Alle, R. J. Gulley, M. J. Brennan, S. J. Buckman, “Detailed theoretical and experimental analysis of low-energy electron-N2 scattering”, Phys. Rev. A., 52:2 (1995), 1229–1256

[9] H. Tagashira, Y. Sakai, S. Sakamoto, “The development of electron avalanches in argon at high E/N values. II. Boltzmann equation analysis”, J. Phys. D: Appl. Phys., 10 (1977), 1051

[10] M. E. Zhukovskiy, R. V. Uskov, “Mathematical modeling of radiative electron emission using hybrid supercomputers”, Numerical methods and programming, 13:1 (2012), 271-279

[11] M. A. Marchenko, G. A. Mikhailov, “Distributed computing by the Monte Carlo method”, Automation and Remote Control, 68:5 (2007), 888-900

[12] M. A. Marchenko, “PARMONC - A Software Library for Massively Parallel Stochastic Simulation”, LNCS, 6873 (2011), 302-315

[13] M. A. Marchenko, G. A. Mikhailov, Page of PARMONC on the web site of Siberian Supercomputer Center } {\tt http://www2.sscc.ru/SORAN-INTEL/paper/2011/parmonc.htm

[14] J. Jeffers, J. Reinders, Intel Xeon Phi Coprocessor High - Performance Programming, Elsevier, 2013, 432 pp.

[15] V. Lisovskiy, J. P. Booth, K. Landry, D. Douai, V. Cassagne, V. Yegorenko, “Electron drift velocity in argon, nitrogen, hydrogen, oxygen and ammonia in strong electric fields determined from rf breakdown curves”, J. Phys. D: Appl. Phys., 39 (2006), 660–665

[16] J. Dutton, “A survey on electron swarm data”, J. Phys. Chem. Ref. Data, 4:3 (1975), 577–851