[2605.23435] MileStone: A Multi-Objective Compiler Phase Ordering Framework for Graph-based IR-Level Optimization

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Computer Science > Programming Languages

arXiv:2605.23435 (cs)

[Submitted on 22 May 2026]

Title:MileStone: A Multi-Objective Compiler Phase Ordering Framework for Graph-based IR-Level Optimization

Authors:Amirhosein Sadr, Mehran Alidoost Nia<br>View a PDF of the paper titled MileStone: A Multi-Objective Compiler Phase Ordering Framework for Graph-based IR-Level Optimization, by Amirhosein Sadr and Mehran Alidoost Nia

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Abstract:Compiler phase ordering has a strong effect on program performance. Finding an effective sequence of passes is still a difficult task because the search space is large and execution time, code size and energy consumption often conflict. Existing methods usually depend on fixed optimization levels or limited heuristics and they rarely handle multiple objectives at the same time. This paper presents MileStone, a modular framework that models compiler phase ordering as a multi-objective optimization problem. MileStone represents programs as graphs, predicts performance metrics with a graph neural network and explores pass sequences with a reinforcement-learning agent that follows user constraints. The framework also builds a self-evolving database that collects compiler transformations and improves prediction quality. Experiments on standard benchmarks show that MileStone finds strong Pareto-optimal solutions, meets energy limits more accurately than LLVM optimization levels and other related techniques. MileStone reduces execution time by up to 45 percent under the same energy budget using a multi-objective approach. The results show that MileStone provides an effective and scalable solution for multi-objective compiler phase ordering.

Subjects:

Programming Languages (cs.PL); Software Engineering (cs.SE)

Cite as:<br>arXiv:2605.23435 [cs.PL]

(or<br>arXiv:2605.23435v1 [cs.PL] for this version)

https://doi.org/10.48550/arXiv.2605.23435

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arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Mehran Alidoost Nia [view email]<br>[v1]<br>Fri, 22 May 2026 09:45:56 UTC (364 KB)

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