How is destructuring transformed\lowered

[ndinsmore]

I think I understand the reasoning but check out the benchmark here

Iterator transformation results in 40% time reduction in Iteration over arrays

Recently it has bugged me that for i in 1:length(array) @inbounds v=array[i] body ... end Was on the order of 30 % faster than: for v in array body ... end So I wanted to see if I could transform the latter into the former. The solution I came up with is a little hacky at the moment but it works & doesn’t change the two argument iterate construct. This has been updated to include a fix to include getindex. # B original iterator type # I new iterator type # IE eltype of I …

@ndinsmore

For the mean time we need the following functions for benchmarking:

function for_sum(iter)
    ret=eltype(iter)(0)
    for v in iter
        ret += v
    end
    return ret
end

# goto_sum is needed because currently for is not lowered with the proper destructuring of next
function goto_sum(iter)
    ret=eltype(iter)(0)
    next = iterate(iter)
    (next === nothing) && @goto loop_end
    @label loop_head
        (v, state) = next
        ret+=v
        next = iterate(iter, state)
        next === nothing &&  @goto loop_end
        @goto loop_head
    @label loop_end
    return ret
end

Lets sanity check their equivlence:

julia> a=collect(1:1000);

julia> for_sum(a)
500500

julia> goto_sum(a)
500500

julia> @benchmark for_sum($a)
BenchmarkTools.Trial: 
  memory estimate:  0 bytes
  allocs estimate:  0
  --------------
  minimum time:     78.688 ns (0.00% GC)
  median time:      83.785 ns (0.00% GC)
  mean time:        91.614 ns (0.00% GC)
  maximum time:     883.004 ns (0.00% GC)
  --------------
  samples:          10000
  evals/sample:     964

julia> @benchmark goto_sum($a)
BenchmarkTools.Trial: 
  memory estimate:  0 bytes
  allocs estimate:  0
  --------------
  minimum time:     78.688 ns (0.00% GC)
  median time:      83.778 ns (0.00% GC)
  mean time:        91.086 ns (0.00% GC)
  maximum time:     793.855 ns (0.00% GC)
  --------------
  samples:          10000
  evals/sample:     957