Reducing Feedback Pollution

Abstract:

Just-in-time compilers enhance the performance of future invocations of a function by generating code tailored to past behavior. To achieve this, compilers use a data structure, often referred to as a feedback vector, to record information about each function’s invocations. However, over time, feedback vectors tend to become less precise, leading to lower-quality code – a phenomenon known as feedback vector pollution. This paper examines feedback vector pollution within the context of a compiler for the R language. We provide data, discuss an approach to reduce pollution in practice, and implement a proof-of-concept implementation of this approach. The preliminary results of the implementation indicate ∼30% decrease in polluted compilations and ∼37% decrease in function pollution throughout our corpus.

BibTeX:

@inproceedings{krynski_reducing_2024,
    title = {{Reducing Feedback Pollution}},
    author = {Krynski, Sebastián and Štěpánek, Michal and Říha, Filip and Křikava, Filip and Vitek, Jan},
    year = {2024},
    booktitle = {{Proceedings of the 16th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages}},
    publisher = {Association for Computing Machinery},
    series = {{VMIL '24}},
    location = {New York, NY, USA},
    doi = {10.1145/3689490.3690404},
    isbn = {9798400712135},
    pages = {65--74},
    url = {https://doi.org/10.1145/3689490.3690404},
}

Proceedings paper