Hi,

I was rewriting some Matlab code into Julia, and I noticed that one function which used array broadcasting operations ran several times slower on Julia. I though this was really strange and I made a simple test function to test broadcasting operations in a few different ways and print the elapsed times. So, the test function is the following:

```
function test_broadcast(M::Int, N::Int, niter::Int=1000)
X = randn(M);
# Case A - simple broadcast
A = zeros(ComplexF64, M, N)
@time begin
for ii = 1:niter
A .+= exp.(im*X)
end
end
# Case B - broadcast with map
B = zeros(ComplexF64, M, N)
@time begin
for ii = 1:niter
B .+= map(x -> exp(x), im*X)
end
end
# Case C - broadcast using the broadcast! function
C = zeros(ComplexF64, M, N)
@time begin
for ii = 1:niter
broadcast!(+, C, C, exp.(im*X))
end
end
# Case D - broadcast using auxiliary variable
D = zeros(ComplexF64, M, N)
@time begin
for ii = 1:niter
Daux = exp.(im*X)
D .+= Daux
end
end
if !all((A .== B) .& (A .== C) .& (A .== D))
throw(ErrorException("Results mismatch"))
end
end
```

when executing this code using for `M = 10000`

and `N = 10`

, I get the following results

```
julia> test_broadcast(10000, 10)
1.826595 seconds (2.00 k allocations: 152.664 MiB, 0.13% gc time)
0.275579 seconds (5.00 k allocations: 305.344 MiB, 1.73% gc time)
0.268911 seconds (4.00 k allocations: 305.328 MiB, 1.74% gc time)
0.269613 seconds (4.00 k allocations: 305.328 MiB, 1.77% gc time)
```

So in this example the case A is roughly 7 times slower than all the other cases.

This code is really simple, I donâ€™t know if I am missing anything. According to the documentation the case A should be equivalent to using the broadcast function. I tried this with Julia versions 1.1, 1.2, and 1.3-rc3, and the results are similar. To me this seems like a bug. I have searched open issues in github and there is this bug https://github.com/JuliaLang/julia/issues/28126 where it seems that there is a problem with broadcasting when using many arrays of the same size, but in my example I only have one array, so it seems that this is a different problem.

This is my output of versioninfo:

```
julia> versioninfo()
Julia Version 1.2.0
Commit c6da87ff4b (2019-08-20 00:03 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-6.0.1 (ORCJIT, skylake)
Environment:
JULIA_EDITOR = "/usr/share/code/code"
```

Any idea of why the case A is much worse?