Add missing parallel=:threads implementations
#429
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What is the issue with using |
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Multithreading typically has lower overhead since it's shared memory. Distributed is usually only worthwhile if you are trying to distribute across multiple machines. |
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Also, Distributed is a stdlib, but stdlibs are still dependencies, and as we have started moving stlibs out of the sysimage, they are becoming more like regular packages. |
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Would this require also bumping the minimum requirement to julia=1.9? I am generally in favor of moving more dependencies to optional dependencies. It makes compilation times much more pleasant as well. |
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #429 +/- ##
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+ Coverage 97.31% 97.38% +0.07%
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Files 117 120 +3
Lines 6956 7007 +51
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+ Hits 6769 6824 +55
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There are compatibility pathways where we only switch to an extension on 1.9+ and keep the hard dependency for earlier versions I think this PR should be ready for review now - it is passing tests for me locally |
FWIW, that kwarg is already there on a lot of other methods, so it's not a new design choice exactly - it was just never provided for these particular operations (because they only had a |
There is some new multi threaded code here - so we probably should take a bit of time to review it - as it can lead to notoriously difficult to spot bugs. |
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Looks mostly good to me. I don't see any race condition
I have added some comments. They are mostly suggestions. In addition:
- We probably should write some documentation for the new
parallelargument. Although I admit that this module is fairly undocumented anyway - and as we don't export anything yet we don't have to be so rigorous.
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These implementations are extremely basic, but they try to follow the patterns in the other parts of the Parallel module. My real motivation is to be able to move the Distributed implementations into an extension, so that Graphs.jl does not depend on Distributed.
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| Base.Threads.@threads for i in 1:vlen | ||
| d = Graphs.dijkstra_shortest_paths(g, vs[i], distmx) | ||
| eccs[i] = maximum(d.dists) | ||
| end |
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It's a bit weird that the end is not covered by the tests - the code inside the loop is, right? If it is indeed then we might just merge it anyways.
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That has been a common issue for me with macro-transformed begin-end blocks. I have never bothered delving into why it is happening though. Macro-heavy libraries like ResumableFunctions.jl and ConcurrentSim.jl suffer from that (and from other more severe macro-covereage issues).
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The PR Pre-Commit Bot failure is a problem with the github action, not this PR. (Probably due to this coming from a fork -- I will look into fixing the action) |
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Anything else needed from me here? |
These implementations are basic, but I tried to follow the patterns in the other parts of the Parallel module.
My real motivation is to be able to move the Distributed implementations into an extension, so that Graphs.jl does not depend on Distributed.