[julia-users] vector assignment performance

[vavasis]

The two functions test4 and test5 below are equivalent, but test5 is much 
faster than test4.  Apparently test4 is carrying out a heap allocation on 
each iteration of the j-loop.  Why?   In general, which kinds of assignment 
statements of the form <array>=<array> create temporaries, and which don't? 
 (In the example below, if the indirect addressing via array i is 
eliminated, then the two functions have comparable performance.)

Thanks,
Steve Vavasis

function test4(n)
    y = [2.0, 6.0, 3.0]
    i = [1, 2, 3]
    z = [0.0, 0.0, 0.0]
    u = 0.0
    for j = 1 : n
        z[:] = y[i]
        u += sum(z)
    end
    u
end    

function test5(n)
    y = [2.0, 6.0, 3.0]
    i = [1, 2, 3]
    z = [0.0, 0.0, 0.0]
    u = 0.0
    for j = 1 : n
        for k = 1 : 3
            z[k] = y[i[k]]
        end
        u += sum(z)
    end
    u
end    


julia> @time Testmv.test4(10000000)
  1.071396 seconds (20.00 M allocations: 1.192 GB, 7.03% gc time)
1.1e8

julia> @time Testmv.test5(10000000)
  0.184411 seconds (4.61 k allocations: 198.072 KB)
1.1e8