Some Insights from a Julia Developer

Re:Some Insights from a Julia Developer by 3JPLW on Saturday October 14, 2017 @07:20PM (#15474883)

This is easily testable:

    julia> using BenchmarkTools
           using OffsetArrays
           A = rand(1000)
           O = OffsetArray(A, 0:999)
           function naive_sum(A)
               s = zero(eltype(A))
               @unsafe for i in eachindex(A) # @unsafe will eventually be folded into @inbounds
                   s += A[i]
               end
               return s
           end
    naive_sum (generic function with 1 method)
    
    julia> @btime naive_sum($A)
      1.025 μs (0 allocations: 0 bytes)
    514.0960505118594
    
    julia> @btime naive_sum($O)
      1.023 μs (0 allocations: 0 bytes)
    514.0960505118594

Yes, there's an extra operation or two in there, but it's effectively free on modern CPUs due to caching/op latencies/pipelining/etc.

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Re:Some Insights from a Julia Developer by StefanKarpinski on Sunday October 15, 2017 @06:02PM (#15479574)

The performance is the same because the core loop in both cases is identical:

    loop:
        vaddsd	(%rcx), %xmm0, %xmm0
        addq	$8, %rcx
        addq	$-1, %rax
        jne	loop

There's more setup required for offset arrays, but otherwise there's no difference. I'm not sure why arrays having an offset would be any more work: array indexing in general involves adding an index to a base pointer; having an offset effectively just changes what the base pointer value is.

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