Thread-safety of ProgressMeter

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
25/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
julia
Domain
distributed-systems

Research direction

Start by reproducing the two examples with Progress, next!, @parallel, @spawn, and fetch to observe where progress updates are delayed or lost. Read the ProgressMeter implementation around Progress and next! and determine the supported behavior for updates from worker processes; done means progress is displayed during the parallel computation rather than only when it returns.

Written by the indexing model from the issue text.

Description

Hi Tim! Me again =)

Is there something special I need to do to use ProgressMeter for parallel computations? I tried something like

function long_running_function()
    n = 100
    p = Progress(n, 1)
    @parallel for i in 1:n
        sleep(0.1)
        next!(p)
    end
end

addprocs(3)

@everywhere using ProgressMeter

long_running_function()

but the call just returned and nothing was printed. I guess it's because p is only defined locally, but I haven't done enough parallel programming in Julia to see intuitively how to make it work on all processes. Adding some @spawn and @fetch calls has some, but not all of the desired, effect - it does print the progress line, but only at the very end, at the same time as the REPL prints the return value.

function long_running_function2()
    n = 100
    p = @spawn Progress(n, 1)
    @parallel for i in 1:n
        sleep(0.1)
        next!(fetch(p))
    end
end
Dominant language
Julia
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Forks
91
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