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2015 | OriginalPaper | Chapter

Hunting Down Load Imbalance: A Moving Target

Author : Christoph Pospiech

Published in: High Performance Computing

Publisher: Springer International Publishing

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Abstract

Load imbalance is known to be a major bottleneck to scalability, particularly when aiming for large parallel partitions. Apart from re-balancing the distribution of the input data, several cures have been proposed. Pretty much all of them assume that the load imbalance is coming from a fixed source. This paper presents an investigation for the climate modelling version CCLM of the weather forecast code COSMO [4]. An adapted MPI trace library is used to collect information about the load imbalance thus introducing a load imbalance measure. Using the visualization software OpenDX [6], this information is correlated to geography and weather forecast results. The resulting pictures show that the locations of high computational load move in space and time. They appear to be correlated to some weather phenomena. In principle this correlation is known for many years [8], but now it has been made visible.

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Literature
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go back to reference Xue, M., Droegemeier, K., Weber, D.: Numerical prediction of high-impact local weather: a driver for petascale computing. In: Petascale Computing: Algorithms and Applications, pp. 103–124 (2007) Xue, M., Droegemeier, K., Weber, D.: Numerical prediction of high-impact local weather: a driver for petascale computing. In: Petascale Computing: Algorithms and Applications, pp. 103–124 (2007)
Metadata
Title
Hunting Down Load Imbalance: A Moving Target
Author
Christoph Pospiech
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-20119-1_35