Large-scale air pollution models, which are normally described mathematically as
systems of partial differential equations, must very often be run efficiently on high-speed
computer architectures. The requirement for efficiency is especially important when some
fine discretization of the spatial domain is to be applied. In practice, this means that an
efficient implementation of such a model on fast modern computers must nearly always be
achieved, because as a rule fine grids are needed in the efforts to avoid the appearance of
numerical errors that are comparable with or even larger than the errors which are caused by
other reasons (uncertainties of the meteorological data, of the emission data, of the rates of
the involved chemical reactions, etc.). The organization of the parallel computations will be
discussed in this chapter of the eBook. The major principles, on which the parallelization is
based, are rather general and, therefore, some of the discussed techniques can also be applied
in connection with some large-scale models arising in other areas of science and
engineering.
Keywords: Balkan Peninsula, Bulgaria, Denmark, England, Hungary, boundary
condition, initial condition, Semi-discretization, sub-models, advection, semi-
Lagrangian discretization, pseudo-spectral discretization, trigonometric polynomials,
truncated Fourier series, Taylor series, QSSA (Quasi-Steady-State-Approximation),
Trapezoidal Rule, Runge-Kutta method, A-stable, Strongly A-stable, L-stable
method, BLAS (Basic Linear Algebra Subroutines), LAPACK, quasi-Newton
iterative method, Cache memory, MPI, OpenMP.
