Revision a121721f975fc4105ed24ebd0ad1020d08d07a38 authored by Shuhei Kadowaki on 01 November 2021, 10:49:07 UTC, committed by GitHub on 01 November 2021, 10:49:07 UTC
* inference: form `PartialStruct` for extra type information propagation This commit forms `PartialStruct` whenever there is any type-level refinement available about a field, even if it's not "constant" information. In Julia "definitions" are allowed to be abstract whereas "usages" (i.e. callsites) are often concrete. The basic idea is to allow inference to make more use of such precise callsite type information by encoding it as `PartialStruct`. This may increase optimization possibilities of "unidiomatic" Julia code, which may contain poorly-typed definitions, like this very contrived example: ```julia struct Problem n; s; c; t end function main(args...) prob = Problem(args...) s = 0 for i in 1:prob.n m = mod(i, 3) s += m == 0 ? sin(prob.s) : m == 1 ? cos(prob.c) : tan(prob.t) end return prob, s end main(10000, 1, 2, 3) ``` One of the obvious limitation is that this extra type information can be propagated inter-procedurally only as a const-propagation. I'm not sure this kind of "just a type-level" refinement can often make constant-prop' successful (i.e. shape-up a method body and allow it to be inlined, encoding the extra type information into the generated code), thus I didn't not modify any part of const-prop' heuristics. So the improvements from this change might not be very useful for general inter-procedural analysis currently, but they should definitely improve the accuracy of local analysis and very simple inter-procedural analysis.
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CITATION.bib
% This article is the definitive citation for Julia.
@article{Julia-2017,
title={Julia: A fresh approach to numerical computing},
author={Bezanson, Jeff and Edelman, Alan and Karpinski, Stefan and Shah, Viral B},
journal={SIAM {R}eview},
volume={59},
number={1},
pages={65--98},
year={2017},
publisher={SIAM},
doi={10.1137/141000671},
url={https://epubs.siam.org/doi/10.1137/141000671}
}
% For more details on research related to Julia, see https://julialang.org/research
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