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Get rid of ThreadsX? #67

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gdalle opened this issue Jun 28, 2023 · 1 comment
Open

Get rid of ThreadsX? #67

gdalle opened this issue Jun 28, 2023 · 1 comment
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enhancement New feature or request

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@gdalle
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gdalle commented Jun 28, 2023

We can speed up loading of InferOpt by replacing ThreadsX with built-in threads:

res = ThreadsX.map(f(i) for i in 1:n)

would become

f1 = f(1)
res = Vector{typeof(f1)}(undef, n)
res[1] = f1
@threads for i in 2:n
    res[i] = f(i)
end

Downsides:

  • less readable code
  • performance hit due to the first element: complexity 1 + (n-1)/t instead of n/t for t threads

Upsides:

  • less dependencies, faster loading of InferOpt
  • improved type stability?
@gdalle gdalle added the enhancement New feature or request label Jun 28, 2023
@gdalle
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gdalle commented Jun 28, 2023

Also beware that @threads sometimes introduces type instabilities due to boxing

JuliaLang/julia#41731

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