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The development of a data-driven application benchmarking approach to performance modelling

Osprey, A., Riley, G. D., Manjunathaiah, M. and Lawrence, B. (2014) The development of a data-driven application benchmarking approach to performance modelling. In: 2014 International Conference on High Performance Computing Simulation (HPCS), 21-25 July 2014, Bologna, Italy, pp. 715-723.

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Abstract/Summary

Performance modelling is a useful tool in the lifeycle of high performance scientific software, such as weather and climate models, especially as a means of ensuring efficient use of available computing resources. In particular, sufficiently accurate performance prediction could reduce the effort and experimental computer time required when porting and optimising a climate model to a new machine. In this paper, traditional techniques are used to predict the computation time of a simple shallow water model which is illustrative of the computation (and communication) involved in climate models. These models are compared with real execution data gathered on AMD Opteron-based systems, including several phases of the U.K. academic community HPC resource, HECToR. Some success is had in relating source code to achieved performance for the K10 series of Opterons, but the method is found to be inadequate for the next-generation Interlagos processor. The experience leads to the investigation of a data-driven application benchmarking approach to performance modelling. Results for an early version of the approach are presented using the shallow model as an example.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
Faculty of Science > School of Mathematical and Physical Sciences > NCAS
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:37708
Uncontrolled Keywords:Analytical models;Bandwidth;Benchmark testing;Computational modeling;Computer architecture;Mathematical model;Meteorology;Performance modelling;benchmarking;multicore;shallow water model

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