[flang] Inline hlfir.matmul[_transpose]. (#122821)

Inlining `hlfir.matmul` as `hlfir.eval_in_mem` does not allow
to get rid of a temporary array in many cases, but it may still be
much better allowing to:
  * Get rid of any overhead related to calling runtime MATMUL
    (such as descriptors creation).
  * Use CPU-specific vectorization cost model for matmul loops,
    which Fortran runtime cannot currently do.
  * Optimize matmul of known-size arrays by complete unrolling.

One of the drawbacks of `hlfir.eval_in_mem` inlining is that
the ops inside it with store memory effects block the current
MLIR CSE, so I decided to run this inlining late in the pipeline.
There is a source commen explaining the CSE issue in more detail.

Straightforward inlining of `hlfir.matmul` as an `hlfir.elemental`
is not good for performance, and I got performance regressions
with it comparing to Fortran runtime implementation. I put it
under an enigneering option for experiments.

At the same time, inlining `hlfir.matmul_transpose` as `hlfir.elemental`
seems to be a good approach, e.g. it allows getting rid of a temporay
array in cases like: `A(:)=B(:)+MATMUL(TRANSPOSE(C(:,:)),D(:))`.

This patch improves performance of galgel and tonto a little bit.

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