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Type Stability in Julia: Avoiding Performance Pathologies in JIT Compilation (Artifact)

Authors: Pelenitsyn, Artem; Belyakova, Julia; Chung, Benjamin; Tate, Ross; Vitek, Jan;

Type Stability in Julia: Avoiding Performance Pathologies in JIT Compilation (Artifact)

Abstract

These code and data (artifact) support the claims of the OOPSLA '21 paper: Type Stability in Julia: Avoiding Performance Pathologies in JIT Compilation ACM DL: DOI: 10.1145/385527 Extended version: arXiv:2109.01950 The way to approach the artifact is described in the Overview.pdf document inside the archive. Any feedback can be posted as issues at the corresponding GitHub repository.

Related Organizations
Keywords

type inference, dynamic languages, method dispatch, compilation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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