By Yu. I. Shokin, M. P. Fedoruk, D. L. Chubarov (auth.), Egon Krause, Yurii I. Shokin, Michael Resch, Nina Shokina (eds.)
This quantity comprises 18 contributions to the 3rd Russian-German complex learn Workshop on Computational technological know-how and excessive functionality Computing offered in July 2007 at Novosibirsk, Russia. The workshop used to be prepared together by way of the excessive functionality Computing middle Stuttgart (HLRS) and the Institute of Computational applied sciences of the Siberian department of the Russian Academy of Sciences (ICT SB RAS) The contributions variety from computing device technological know-how, arithmetic and excessive functionality computing to functions in mechanical and aerospace engineering. They convey a wealth of theoretical paintings and simulation event with a possible of bringing jointly theoretical mathematical modelling and utilization of excessive functionality computing structures offering the cutting-edge of computational technologies.
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Additional info for Computational Science and High Performance Computing III: The 3rd Russian-German Advanced Research Workshop, Novosibirsk, Russia, July 23 - 27, 2007
I. P. D. V. Shaidurov2 1 Institute of Numerical Mathematics RAS, Gubkina st. ru Abstract. The inverse problem of the mathematical theory of tides is considered in the form of defining a boundary values on liquid parts of boundary. The direct and conjugate equations of shallow water are closed by the observation data on the function of sea level (free surface elevation) on a part of the boundary. The iterative algorithm is used for solving this complete problem in connection to tides of World Ocean.
4 Discrete Analogues of Variational Problems In order to construct the discrete analogue of the variational problem, the elements of the space H(rot; Ω) are approximated by the elements of the discrete space Hh (rot; Ω). Let us introduce the discrete analogue of the variational problem. ∈ L2 (Ω)3 find Discrete variational problem. For J0re h h h h h h Ere ∈ H0 (rot; Ω) and Eim ∈ H0 (rot; Ω) such that ∀v1 ∈ H0 (rot; Ω) and ∀v2h ∈ Hh0 (rot; Ω): (μ−1 ∇ × Ehre , ∇ × v1h )Ω − (ω 2 εEhre , v1h )Ω − (ωσEhim , v1h )Ω = 0, (μ−1 ∇ × Ehim , ∇ × v2h )Ω − (ω 2 εEhim , v2h )Ω + (ωσEhre , v2h )Ω = (ωJ0re , v2h )Ω .
Comp. Science & High Perf. Computing III, NNFM 101, pp. 44–51, 2008. com Hardware Development and Impact on Numerical Algorithms 2 45 Hardware Development Aggregating peak performance seems to be simple in the ongoing development. The important question is how to transmit this high potential to existing algorithms. It turns out that memory hierarchies and the interconnection of core local memories will play in important role. We begin with an interesting but outdated concept, give a highlight on a “many core” chip, report some essential properties of the Cell processor, collect the rumors on an Intel concept, show some properties of future NEC vector processors and make remarks on graphic card processors.