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Correct distributed computing section typos #135

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May 30, 2025
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Correct distributed computing section typos #135

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6 changes: 3 additions & 3 deletions optimizing/index.md
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Expand Up @@ -372,9 +372,9 @@ Some widely used parallel programming packages like [LoopVectorization.jl](https

### Distributed computing

Julia's multiprocessing and distributed relies on the standard library `Distributed`.
The main difference with multi-threading is that data isn't shared between worker processes.
Once Julia is started, processes can be added with `addprocs`, and their can be queried with `nworkers`.
Julia's multiprocessing and distributed computing relies on the standard library `Distributed`.
The main difference compared to multi-threading is that data isn't shared between worker processes.
Once Julia is started, processes can be added with `addprocs`, and they can be queried with `nworkers`.

The macro `Distributed.@distributed` is a _syntactic_ equivalent for `Threads.@threads`.
Hence, we can use `@distributed` to parallelise a for loop as before, but we have to additionally deal with sharing and recombining the `results` array.
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