Performance of variants of findall

#1

Here is a small session:

julia> using BenchmarkTools

julia> A = rand(100, 100)
100×100 Array{Float64,2}  [...]

julia> @btime findall(A .> 0.5)
  39.951 μs (7 allocations: 85.06 KiB)
5077-element Array{CartesianIndex{2},1}  [...]

julia> @btime findall(x -> x > 0.5, A)
  208.314 μs (17 allocations: 256.80 KiB)
5077-element Array{CartesianIndex{2},1} [...]

Why these timing differences between evaluations of two expressions that look so close and sensible ?

#2

They are not the same (you can explore this with @edit, or the debugger). The first creates a temporary array for A .> 0, and then collects the true indexes. Both of these operations are very fast.

The second one goes through the generic iterator path. Perhaps it could optimized more, I am sure PRs doing this would be welcome.

#3

Thanks for your answer. Perhaps some warning in the documentation (https://docs.julialang.org/en/v1/base/arrays/#Base.findall-Tuple{Function,Any}), about the case where the second argument is an array, would be useful.

#4

Try to see if there is any effect of interpolating A into the expression with $

#5

I don’t think there is an inherent reason for the performance difference here (which would of course warrant documentation), it is just waiting for someone to optimize it.

#6

See also the similar topic Comprehension vs map and filter unexpected speeds

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