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TuningGenie: Auto-Tuning Framework Based on Rewriting Rules

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Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2014)

Abstract

This paper presents results on development of the auto-tuning framework named TuningGenie aimed at automating adjustment of parallel tasks to target platform. The framework works with source code of parallel software and performs source-to-source transformations by using facilities of a rule-based rewriting system. This approach significantly raises flexibility of proposed solution and enables changing computation structure of a tuned program in a declarative way. The framework’s architecture, lifecycle, offered toolset for optimization, demo examples and results of tuning of a computationally complex task of short-term meteorological forecasting are presented.

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Correspondence to Pavlo A. Ivanenko .

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Ivanenko, P.A., Doroshenko, A.Y., Zhereb, K.A. (2014). TuningGenie: Auto-Tuning Framework Based on Rewriting Rules. In: Ermolayev, V., Mayr, H., Nikitchenko, M., Spivakovsky, A., Zholtkevych, G. (eds) Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2014. Communications in Computer and Information Science, vol 469. Springer, Cham. https://doi.org/10.1007/978-3-319-13206-8_7

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  • DOI: https://doi.org/10.1007/978-3-319-13206-8_7

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