Guiding Inlining Decisions Using Post-Inlining Transformations

  • Author / Creator
    Ochoa, Erick E
  • Inlining strategies in JIT compilers have relied on a mixture of heuristics and frequency information to discriminate between inlining candidates. Even though nested inlining is the norm in JIT compilers, modeling inlining as a variation of the greedy knapsack algorithm provides sub-optimal solutions. Recent advancements by Craik et al. allow for solutions for the nested inlining problem, however, they require grading inlining candidates based on an abstract notion of "benefit". In this thesis, we define this abstract notion of "benefit" through the use of static analysis and frequency information. The choice of using static analysis instead of heuristics has consequences on the guarantees that an inlining strategy provides and on the compilation time incurred by the compiler. We show that our proposed static analysis is comparable to heuristics in terms of compilation time, memory resources used during compilation, and impact on run time. While our proposed inlining strategy increased run time by 4% compared to the default inlining strategies found in the OpenJ9 JVM, our inlining strategy allows compiler engineers to fine tune the abstract notion of "benefit" and provides human readable reports that show why inlining decisions were taken. The number of proposed inlining plans that differ between the heuristics and the static analyses is small, however, it provides a lower bound for how more powerful static analyses may improve inlining in the future.

  • Subjects / Keywords
  • Graduation date
    Fall 2019
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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