Refactoring for Performance with Semantic Patching: Case Study with Recipes

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High Performance Computing (ISC High Performance 2021)

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Abstract

Development of an HPC simulation code may take years of a domain scientists’ work. Over that timespan, the computing landscape evolves, efficient programming best practices change, APIs of performance libraries change, etc. A moment then comes when the entire codebase requires a thorough performance lift. In the luckiest case, the required intervention is limited to a few hot loops. In practice, much more is needed. This paper describes an activity of programmatic refactoring of \(\approx \)200k lines of C code by means of source-to-source translation. The context is that of a so-called high level support provided to the domain scientist community by a HPC service center. The motivation of this short paper is the immediate reuse potential of these techniques.

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Correspondence to Michele Martone .

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Martone, M., Lawall, J. (2021). Refactoring for Performance with Semantic Patching: Case Study with Recipes. In: Jagode, H., Anzt, H., Ltaief, H., Luszczek, P. (eds) High Performance Computing. ISC High Performance 2021. Lecture Notes in Computer Science(), vol 12761. Springer, Cham. https://doi.org/10.1007/978-3-030-90539-2_15

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  • DOI: https://doi.org/10.1007/978-3-030-90539-2_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90538-5

  • Online ISBN: 978-3-030-90539-2

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