Papers › Automated Code Optimization with E-Graphs

Automated Code Optimization with E-Graphs

26 Dec 2021arXiv:2112.14714links table onlyarchive 2025-07-28

Alessandro Cheli

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This thesis proposes an advanced, generic and high-level code rewriting and analysis system in the Julia programming language, providing applied equality saturation in the presence of multiple dispatch and metaprogramming. We show how our system can practically solve some challenging problems: Can programmers implement their own high-level compiler optimizations for their domain-specific scientific programs, without the requirement of them being compiler experts at all? Can these optimizers be implemented by users in the same language and inside the same programs they want to optimize, solving the two-language problem? Can these compiler optimizers be written in a high-level fashion, as equations, without the need to worry about the rewriting ordering? Thus, can symbolic mathematics do high-level compiler optimizations or vice-versa?

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juliasymbolics/metatheory.jl officialmentioned in papermentioned on GitHubMIT report
0x0f0f0f/Metatheory.jl mentioned on GitHubMIT report

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