Help with parallelizing indirect inference estimation

[tkf]

@mcreel

    m = zeros(size(x,2))
    Threads.@threads for i in 1:M
    #for i in 1:M
    m .+= ols(x,ys[i])
    end

m .+= ... causes a data race. Every thread tries to update every element in m.

If you need a parallel sum, checkout Folds.sum or FLoops.@reduce.

@amrods

Is there a way to add threads to Julia after it is started?

This is not possible at the moment. It’d require a rather large surgery to the Julia runtime.

@amrods

@floop for i in 1:size(x, 1)

You’d need @floop ThreadedEx() for i in 1:size(x, 1). Similar Q/A Problem with `@reduce` of `FLoops`; data race? - #2 by tkf