A Two-step Approach to Find Short Compilation Transformation Sequences for Optimal Software Runtime Performance

More efficient programs can be obtained by applying compiler optimization flags, i.e., sequences of code transformations. However, these generic sequences often underperform, as their effectiveness depends on both the software and hardware characteristics. This highlights the need for tailored transformation sequences. This paper introduces a new problem composed of two combinatorial optimization tasks aimed at finding optimal and minimal-length source code transformation sequences. Shorter sequences enable faster compilation using only the most effective transformations for a given program and hardware. We propose a two-step methodology to solve the problem: first, find sequences that minimize program runtime; second, reduce their length without degrading performance. Our approach produces sequences up to 51.27% shorter and over 26% faster compared to the -O3 flag.

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Publication Details

Journal
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Published
2025-07-14
DOI
https://doi.org/10.1145/3712255.3726624
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

A Two-step Approach to Find Short Compilation Transformation Sequences for Optimal Software Runtime Performance

Patricia Ruiz, José Miguel Aragón-Jurado, Javier Jareño, Bernabè Dorronsoro et al.
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Distributed and Parallel Computing Systems
article

A Two-step Approach to Find Short Compilation Transformation Sequences for Optimal Software Runtime Performance

Patricia Ruiz, José Miguel Aragón-Jurado, Javier Jareño, Bernabè Dorronsoro, Juan Carlos de la Torre
article en

Abstract

More efficient programs can be obtained by applying compiler optimization flags, i.e., sequences of code transformations. However, these generic sequences often underperform, as their effectiveness depends on both the software and hardware characteristics. This highlights the need for tailored transformation sequences. This paper introduces a new problem composed of two combinatorial optimization tasks aimed at finding optimal and minimal-length source code transformation sequences. Shorter sequences enable faster compilation using only the most effective transformations for a given program and hardware. We propose a two-step methodology to solve the problem: first, find sequences that minimize program runtime; second, reduce their length without degrading performance. Our approach produces sequences up to 51.27% shorter and over 26% faster compared to the -O3 flag.

Proceedings of the Genetic and Evolutionary Computation Conference Companion
Universidad de Cádiz (ES)
Ministerio de Ciencia, Innovación y Universidades, Ministerio de Ciencia, Tecnología e Innovación Productiva
Openalex Percentile: Top 45%
Distributed and Parallel Computing Systems
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