JuliaSIMD / JuliaSIMD/LoopVectorization.jl

Problem/error in execution order

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Description

I observe that the following MWE code works differently with vs without the tturbo.
```
using LoopVectorization, Random
function weird_update(a, c, d)
@tturbo for j in axes(a, 2)
tmp = 0.0
for i in axes(a, 1)
a_ij = a[i, j]
b_ij = a_ij + 1.0
tmp += b_ij^2
end
c[j] = tmp
d[j] = exp(2.0*tmp)
end
return nothing
end
m = 100
n = 5
rng = MersenneTwister(0)
a = zeros(n, m)
randn!(rng, a)
c = zeros(m)
d = zeros(m)
weird_update(a, c, d)
println(c)
println(d)
```
In fact, with tturbo, `d` is always 1, as if the code for updating `d` is written after `tmp=0.0`. On the other hand, the update for `c` works well.

Could you help me figure out a way to do this correctly with tturbo?

UPDATE1: it is weird that if I change `d[j] = exp(2.0*tmp)` to `d[j]=exp(2.0*(0.0+tmp))`, then it works correctly.

UPDATE2: The following code works even more weirdly
```
function weird_update(a, c, d)
@tturbo for j in axes(a, 2)
tmp = 0.0
for i in axes(a, 1)
a_ij = a[i, j]
b_ij = a_ij + 1.0
tmp += b_ij^2
end
c[j] = tmp
d[j] = exp(2.0*c[j])

end
return nothing
end
m = 100
n = 5
rng = MersenneTwister(0)
a = zeros(n, m)
randn!(rng, a)
c = ones(m)
d = zeros(m)
weird_update(a, c, d)
println(c)
println(d)
```
The output of `d` is all one's -- not even `exp(2)`. I am totally confused.

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