Performance of mixed-type (matrix-) multiplication

Hi,

I noticed that mixed-type multiplication (e.g. *(::SMatrix, ::Matrix)) is slow. I searched the issues but didn't find one that mentions this.
For example:

julia> SA = @SMatrix randn(3,3);

julia> A = Matrix(SA);

julia> B = randn(3, 1_000);

julia> @btime $SA * $B;
  14.455 μs (5 allocations: 54.23 KiB)

julia> @btime $A * $B;
  2.121 μs (2 allocations: 23.48 KiB)

This is, because *(::SMatrix, ::Matrix) doesn't hit BLAS and goes via LinearAlgebra.generic_matmul!().
This case doesn't seem to be covered by the benchmarks (unless I missed it), so I'm wondering whether it would it be in scope (of this package) to address this.
If not, I think it should be mentioned somewhere though.
Note that converting to standard Array followed by Matrix-Matrix multiplication is much faster than the SMatrix-Matrix multiplication (because it hits BLAS), and allocates less:

julia> @btime Matrix($SA) * $B;
  2.062 μs (3 allocations: 23.61 KiB)

Start by reproducing the reported benchmarks for SMatrix–Matrix multiplication and compare them with Matrix–Matrix multiplication. Read LinearAlgebra.generic_matmul! and the package's existing multiplication benchmarks, then determine whether the intended result is faster mixed-type multiplication or documentation of the limitation. Done means the chosen direction is covered by a benchmark and its performance or documentation is verified.