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Optimize knownProducts for direct-to-JAR compilation #939

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merged 3 commits into from
Nov 9, 2020

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@retronym retronym commented Nov 3, 2020

Fixes #933

@retronym retronym force-pushed the faster/classes-in-jar branch from 609618f to 46d2659 Compare November 3, 2020 06:45
@retronym retronym marked this pull request as ready for review November 3, 2020 08:03
Comment on lines 1101 to 1102
def knownProductsPar =
if (AnalysisCallback.parallelKnownProducts) new ParVector(knownProducts) else knownProducts
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Does this use the default fork/join scheduler? If so, could it end up competing against other tasks or potentially other Zinc compilation that are also trying to do the same thing? Or it finishes quickly enough that it won't surface? (But takes long enough time if it's not parallelized?)

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Looks like I added the parallel thing in 94ba81e, but I'd be happy to see it gone if it's not working.

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@retronym retronym Nov 9, 2020

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In this case I think the best idea is to keep it sequential. If this is a bottle neck, we can try to first reduce the overhead in sequential code (like I've done here, but I'm sure there are more opportunities.) Sequential code is a bit easier to profile and tune. Using parallelism should be done with a careful understanding of whether the task size suitable for parallel collections (e.g. something like (1 to 1000).par.count(_ % 2 == 0) is slower than the sequential version.

I've added a commit to remove the ParVector altogether.

@retronym retronym force-pushed the faster/classes-in-jar branch from f0b62bd to f00ef7d Compare November 9, 2020 05:41
@retronym retronym requested a review from eed3si9n November 9, 2020 06:11
@eed3si9n eed3si9n merged commit 6bcaba0 into sbt:develop Nov 9, 2020
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Performance improvement ideas for Zinc 1.4.x
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