Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
Large Scale Computations in Air Pollution Modelling
Large Scale Computations in Air Pollution Modelling
Massive data set issues in air pollution modelling
Handbook of massive data sets
An Algorithm for Parallel Implementations of an Eulerian Smog Model
NMA '02 Revised Papers from the 5th International Conference on Numerical Methods and Applications
Parallel runs of a large air pollution model on a grid of Sun computers
Mathematics and Computers in Simulation
Large-scale computations with the unified danish eulerian model
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
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Mathematical models for large-scale air pollution studies consist of systems of partial differential equations (PDEs). The number of equations in these systems of PDEs is equal to the number of chemical compounds (the number of chemical compounds involved in the current large-scale air pollution models varies from 20 to about 200). The space domain of the systems of PDEs is normally very large, because the models must be able to treat transboundary long-range transport of the harmful pollutants. The time-intervals are often very long (runs with meteorological data covering up to 10 years have sometimes to be carried out). Moreover, fine spatial and temporal resolution is as a rule required. This leads to very large computational tasks when the air pollution models are discretized. Therefore, it is necessary to use fast and sufficiently accurate numerical methods as well as to exploit efficiently the great potential power of the parallel computers. Some results, which are obtained when several versions of a large-scale air pollution model are run on different parallel architectures, will be presented in this paper.