Slow multiplication of reshaped matrices

Compare:

```
v = randn(728, 600)
w = randn(70, 728)
@time w * v # 0.017802 seconds (2 allocations: 328.172 KiB)
```

with:

```
v_ = reshape(reshape(v', 600, 728)', 728, 600)
w_ = reshape(reshape(w', 728, 70)', 70, 728)
@time w_ * v_ 0.161401 seconds (5 allocations: 358.922 KiB)
```

The second one is 10x slower. Note that the underlying data in memory is exactly the same, and with the same layout.

Can the reshape / adjoint type signature be simplified here?

Start by running the two Julia benchmark snippets in the issue and confirm the reported multiplication slowdown. Then inspect the reshape/adjoint type-signature path implicated by the report; done means the reshaped matrices no longer show the roughly 10x slowdown while retaining the same underlying layout.

Written by the indexing model from the issue text.