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Genetic Improvement of LLVM Intermediate Representation

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Genetic Programming (EuroGP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13986))

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Abstract

Evolving LLVM IR is widely applicable, with LLVM Clang offering support for an increasing range of computer hardware and programming languages. Local search mutations are used to hill climb industry C code released to support geographic open standards: Open Location Code (OLC) from Google and Uber’s Hexagonal Hierarchical Spatial Index (H3), giving up to two percent speed up on compiler optimised code.

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Notes

  1. 1.

    In [38] we used a similar idea to test if mutated code is identical by inspecting X86 assembler generated by the GNU gcc compiler. Also Mike Papadakis et al. [39] compared compiler output to look for equivalent mutants.

  2. 2.

    https://github.com/google/open-location-code downloaded 4 August 2022.

  3. 3.

    https://github.com/uber/h3 downloaded 3 August 2022.

  4. 4.

    https://www.getthedata.com/downloads/open_postcode_geo.csv.zip dated 16 March 2022. The data are alphabetically sorted starting with AB1 0AA, which is in Aberdeen.

  5. 5.

    Mutable conditional br instructions give rise to two mutations per line, Sect. 3.1.

  6. 6.

    Our LLVM IR representation allows ready calculation of how many lines of LLVM IR are impacted, as an alternative to counting the number of mutations.

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Acknowledgements

We are grateful for help from H.Wierstorf (gnuplot) and F.Pfenning (\(\phi \) nodes). Funded by the Meta Oops project.

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  1. CREST, Department of Computer Science, UCL, Gower Street, London, WC1E 6BT, UK

    William B. Langdon, Afnan Al-Subaihin, Aymeric Blot & David Clark

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Correspondence to William B. Langdon .

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  1. Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

    Gisele Pappa

  2. Università degli studi di Torino, Turin, Italy

    Mario Giacobini

  3. Brno University of Technology, Brno, Czech Republic

    Zdenek Vasicek

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Langdon, W.B., Al-Subaihin, A., Blot, A., Clark, D. (2023). Genetic Improvement of LLVM Intermediate Representation. In: Pappa, G., Giacobini, M., Vasicek, Z. (eds) Genetic Programming. EuroGP 2023. Lecture Notes in Computer Science, vol 13986. Springer, Cham. https://doi.org/10.1007/978-3-031-29573-7_16

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