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opt: sig anyval#4614

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Draft
coreyoconnor wants to merge3 commits intoscala-native:main
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@coreyoconnor
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Adopted from comment and PR

UsingVM version: JDK 21.0.8, OpenJDK 64-Bit Server VM, 21.0.8+9-nixos

Based purely on the JMH bench results this does not have a measurable impact. Leaving as draft to answer conversation.

tools-benchmark/jmh:run -i 20 scala.scalanative.benchmarks.LinkerBench

Prior

[info] Result "scala.scalanative.benchmarks.LinkerBench.link":[info]   1126.626 ±(99.9%) 55.782 ms/op [Average][info]   (min, avg, max) = (1068.876, 1126.626, 1376.822), stdev = 64.238[info]   CI (99.9%): [1070.844, 1182.408] (assumes normal distribution)[info] # Run complete. Total time: 00:01:03[info] Result "scala.scalanative.benchmarks.LinkerBench.link":[info]   1126.626 ±(99.9%) 55.782 ms/op [Average][info]   (min, avg, max) = (1068.876, 1126.626, 1376.822), stdev = 64.238[info]   CI (99.9%): [1070.844, 1182.408] (assumes normal distribution)[info] # Run complete. Total time: 00:01:03

Post

[info] Result "scala.scalanative.benchmarks.LinkerBench.link":[info]   1166.456 ±(99.9%) 142.858 ms/op [Average][info]   (min, avg, max) = (1049.574, 1166.456, 1521.616), stdev = 164.516[info]   CI (99.9%): [1023.598, 1309.314] (assumes normal distribution)[info] # Run complete. Total time: 00:01:03
[info] Result "scala.scalanative.benchmarks.LinkerBench.link":[info]   1113.939 ±(99.9%) 107.734 ms/op [Average][info]   (min, avg, max) = (1026.294, 1113.939, 1468.061), stdev = 124.066[info]   CI (99.9%): [1006.206, 1221.673] (assumes normal distribution)[info] # Run complete. Total time: 00:01:00

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@LeeTibbert
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LeeTibbert commentedNov 1, 2025•
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coreyoconnor.

Could you take a moment to explain to a interested reader who is not a subject expert a few things?
I appreciate 3 minutes of your time. Thank you.

It appear that you are trying to speed up the SN link phase by implementing a suggestion by Densh.
Such a speed up would certainly be a good thing. It certainly would save me time for I use that
phase many times a day.

These are probably perfectly obvious to you.

  1. Exactly what is being measured?

  2. The answer is probably in the supplied "scala.scalanative.benchmarks.LinkerBench",
    but that is not a link and I tracking it down would take more time than available.

  3. What is the direction of goodness? Are larger numbers better?

From what I see, the bottom set has a greater dispersion and a mean that is
greater in one case and less in another. Hard to see a win either direction
of goodness.

@WojciechMazur
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Definitely makes sense but also breaks binary compatibility. Would need to wait for the next minor release.

@coreyoconnor
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I'm attempting to gather more info on allocations and actual profiling info.

Unfortunately my computer hard locks when i try to profile anything! Not what i wanted to spend my time on haha.

Anyways, I'll be updating this with further analysis once my computer can handle it.

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@coreyoconnor@LeeTibbert@WojciechMazur
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