Slowdown with views in 0.12.119

I have a reimplementation of `Linearlagebra.qr` in my codebase which uses `@turbo`. In it there is

```julia
using LinearAlgebra, LoopVectorization, BenchmarkTools

function reflectorApply!(x::AbstractVector{<: Real}, τ::Real, A::StridedMatrix{<: Real})
m, n = size(A)
@inbounds for j = 1:n
# dot
vAj = A[1, j]
@turbo for i = 2:m
vAj += conj(x[i]) * A[i, j]
end

vAj = conj(τ)*vAj

# ger
A[1, j] -= vAj
@turbo for i = 2:m
A[i, j] -= x[i]*vAj
end
end
return A
end
```

which is called with two views into the same array:

```julia
input = rand(64, 64)
n = 64
j = 17
τ = 1.7
x = LinearAlgebra.view(input, j:n, j)
y = LinearAlgebra.view(input, j:n, j+1:n)
@benchmark reflectorApply!($x, $τ, $y)
```

I've noticed that after triggering a package update things have been running more slowly and Identified that the problem is here. Trying some different version of LoopVectorization pointed showed that v0.12.119 had made this much slower:

```julia
# median times via @benchmark, after julia restart
# no turbo: 2.9µs
# 0.12.124: 48µs
# 0.12.120: 46µs
# 0.12.119: 46µs
# 0.12.118: 0.72µs
# 0.12.115: 0.74µs
# 0.12.110: 0.72µs
# 0.12.100: 0.71µs
```

Rewriting this to use no views restores the performance from before 0.12.119.

Start by reproducing the @benchmark for reflectorApply! with x and y as views into the same input array, then compare LoopVectorization 0.12.118 with 0.12.119 and later versions. Done means identifying why the viewed-array case regressed and restoring performance near the pre-0.12.119 measurements without views losing their prior behavior.

Scritto dal modello di indicizzazione a partire dal testo della issue.