Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
Computational challenges in large-scale air pollution modelling
ICS '01 Proceedings of the 15th international conference on Supercomputing
Parallel Implementation of a Large-Scale 3-D Air Pollution Model
LSSC '01 Proceedings of the Third International Conference on Large-Scale Scientific Computing-Revised Papers
Computational complexity of weighted splitting schemes on parallel computers
International Journal of Parallel, Emergent and Distributed Systems
Numerical Analysis and Its Applications
Parallel and GRID implementation of a large scale air pollution model
NMA'06 Proceedings of the 6th international conference on Numerical methods and applications
Parallel implementation and one year experiments with the danish eulerian model
NAA'04 Proceedings of the Third international conference on Numerical Analysis and its Applications
Dynamic load-balancing for the STEM-II air quality model
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
Adjoint computations in data assimilation problems using a 4-stage rosenbrock method
LSSC'05 Proceedings of the 5th international conference on Large-Scale Scientific Computing
Runs of UNI–DEM model on IBM blue gene/p computer and analysis of the model performance
LSSC'09 Proceedings of the 7th international conference on Large-Scale Scientific Computing
LSSC'09 Proceedings of the 7th international conference on Large-Scale Scientific Computing
LSSC'11 Proceedings of the 8th international conference on Large-Scale Scientific Computing
Parallel computation of sensitivity analysis data for the danish eulerian model
LSSC'11 Proceedings of the 8th international conference on Large-Scale Scientific Computing
| Hi-index | 0.00 |
Large scale air pollution models are powerful tools, designed to meet the increasing demand in different environmental studies. The atmosphere is the most dynamic component of the environment, where the pollutants can quickly be moved in a very long distance. Therefore the advanced modeling must be done in a large computational domain. Moreover, all relevant physical, chemical and photochemical processes must be taken into account. The speed of these processes vary in a wide range. This fact implies that a small time step must be used in order to achieve both numerical stability and sufficient accuracy of the results. Thus the numerical treatment of such an air pollution model becomes in many cases a huge computational problem, a challenging task for the most powerful up-to-date supercomputers.The Danish Eulerian Model (DEM) is used in this work. The paper focuses on the efficient parallel implementation of DEM on powerful parallel supercomputers. We present a variety of performance and scalability results, obtained on different parallel machines by using standard parallelization tools (MPI for distributed-memory parallelism and OpenMP for shared-memory parallelism). It is shown by experiments that MPI and OpenMP can both be used on separate levels of parallelism to get the best use of the clustered parallel machines. Application of the results in the environmental studies, related to high ozone concentrations in the air, is illustrated by some plots in the last section.