A Three-Stage Genetic Algorithm for Compiler Flag and Library Version Selection to Minimize Execution Time

Existing research in compiler autotuning mainly focuses on selecting optimization flags without configurable values. However, the potential of selecting optimization flags with configurable values, alongside using directory and link flags for library version selection to improve performance, remains largely unexplored. We propose a three-stage Genetic Algorithm (GA) that incrementally selects optimization flags without configurable values, then optimization flags with configurable values, and finally library versions, to minimize software execution time. We also discuss the implementation challenges of the proposed algorithm and outline potential future work.

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Publication Details

Published
2025-04-27
DOI
https://doi.org/10.1109/gi66624.2025.00009
Citations
1
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
3.25
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article

A Three-Stage Genetic Algorithm for Compiler Flag and Library Version Selection to Minimize Execution Time

Chi Hou Chan, Spyro Nita
1 citations
Software Engineering Research
3.25
article

A Three-Stage Genetic Algorithm for Compiler Flag and Library Version Selection to Minimize Execution Time

Chi Hou Chan, Spyro Nita
article en
1 citations

Abstract

Existing research in compiler autotuning mainly focuses on selecting optimization flags without configurable values. However, the potential of selecting optimization flags with configurable values, alongside using directory and link flags for library version selection to improve performance, remains largely unexplored. We propose a three-stage Genetic Algorithm (GA) that incrementally selects optimization flags without configurable values, then optimization flags with configurable values, and finally library versions, to minimize software execution time. We also discuss the implementation challenges of the proposed algorithm and outline potential future work.

Edinburgh Napier University (GB), El Paso Community College (US), University of Edinburgh (GB)
Openalex Percentile: Top 8%
Software Engineering Research
3.25
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