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Runs of UNI–DEM Model on IBM Blue Gene/P Computer and Analysis of the Model Performance

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Large-Scale Scientific Computing (LSSC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5910))

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Abstract

UNI–DEM is an Eulerian model for studying long range transport of air pollutants. The computational domain of the model covers Europe and some neighbour parts of Atlantic ocean, Asia and Africa. The model mainly is developed in the National Environmental Research Institute of Denmark, located at Roskilde. If UNI–DEM model is to be applied on a large space domain by using fine grids, then its discretization leads to a huge computational problem. If the space domain is discretized by using a (480 x 480) grid and the number of chemical species studied by the model is 35, then several systems of ordinary differential equations containing 8 064 000 equations have to be treated at every time-step (the number of time-steps being typically several thousand). If a three-dimensional version of the same air pollution model is to be used, then the figure above must be multiplied by the number of layers. This implies that such a model as UNI–DEM must be run only on high-performance computer architectures, like IBM Blue Gene/P. The implementatation of such complex large–scale model on each new computer is a non trivial task. Analysis of the runs of UNI–DEM performed until now on IBM Blue Gene/P computer is presented and some preliminary results on performance, speed ups and efficiency are discussed.

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Georgiev, K., Zlatev, Z. (2010). Runs of UNI–DEM Model on IBM Blue Gene/P Computer and Analysis of the Model Performance. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2009. Lecture Notes in Computer Science, vol 5910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12535-5_21

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  • DOI: https://doi.org/10.1007/978-3-642-12535-5_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12534-8

  • Online ISBN: 978-3-642-12535-5

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