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use @everywhere in distributed bootstrap example #764

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Apr 23, 2024
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use @everywhere in distributed bootstrap example #764

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9 changes: 8 additions & 1 deletion docs/src/bootstrap.md
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Expand Up @@ -163,13 +163,20 @@ For computers with many processors (as opposed to a single processor with severa

```@example Main
using Distributed
using ProgressMeter
# you already have 1 proc by default, so add the number of additional cores with `addprocs`
# you need at least as many RNGs as cores you want to use in parallel
# but you shouldn't use all of your cores because nested within this
# is the multithreading of the linear algebra
# addprocs(1)
@info "Currently using $(nprocs()) processors total and $(nworkers()) for work"

# Load the necessary packages on all workers
# For clusters, you will also need to make sure that the Julia
# environment (Project.toml) is set up and activated on each worker.
@everywhere begin
using ProgressMeter
using MixedModels
end
# copy everything to workers
@showprogress for w in workers()
remotecall_fetch(() -> coefnames(m2), w)
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