RUNNING AIR-POLLUTION MODELS ON MASSIVELY-PARALLEL MACHINES

The concentration of air pollutants have in general been steadily incr easing during the last three decades. To correctly gauge the impact of various sources of pollutants requires careful modelling of the compl ex physics processes associated with the chemistry and transport of ai r pollution. These models are computationally demanding and require to day's fastest high performance computers for practical implementations . The damaging effects are normally due to the combined effects of sev eral air pollutants. Therefore a reliable mathematical model must stud y simultaneously all relevant air pollutants. This requirement increas es the size of the air pollution models. The discretization of models that contain many air pollutants leads to huge computational problems. After the discretization of such an air pollution model, systems of s everal hundred thousands (or even several millions) of equations arise and these have to be treated numerically during many time-steps (typi cally several thousands). Such big computational problems can successf ully be treated only on big modern vector and/or parallel computers. H owever, access to a fast high-speed computer is not sufficient. One mu st also ensure that the great potential power of the computer is corre ctly exploited. Very often this is a rather difficult task. The effort s to solve this task in the case where the computer under consideratio n is a massively parallel machine will be discussed in this paper. Tes ts performed on several such computers will be presented.