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6 changes: 3 additions & 3 deletions doc/src/manual/parallel-computing.md
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Expand Up @@ -16,14 +16,14 @@ Julia also supports experimental multi-threading, where execution is forked and
threads.
Known as the fork-join approach, parallel threads execute independently, and must ultimately be joined in Julia's main thread to allow serial execution to continue.
Multi-threading is supported using the `Base.Threads` module that is still considered experimental, as Julia is
not yet fully thread-safe. In particular segfaults seem to occur during I/O operations and task switching.
not yet fully thread-safe. In particular,segfaults seem to occur during I/O operations and task switching.
As an up-to-date reference, keep an eye on [the issue tracker](https://github.com/JuliaLang/julia/issues?q=is%3Aopen+is%3Aissue+label%3Amultithreading).
Multi-Threading should only be used if you take into consideration global variables, locks and
atomics, all of which are explained later.

In the end we will present Julia's approach to distributed and parallel computing. With scientific computing
In the end,we will present Julia's approach to distributed and parallel computing. With scientific computing
in mind, Julia natively implements interfaces to distribute a process across multiple cores or machines.
Also we will mention useful external packages for distributed programming like `MPI.jl` and `DistributedArrays.jl`.
Also, we will mention useful external packages for distributed programming like `MPI.jl` and `DistributedArrays.jl`.

# Coroutines

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