Tensor product operations: Use loop unrolling for slow mat-vec

[kronbichler]

This is the optimization I mentioned in #16970: For the simplex elements and good performance of the matrix-free evaluation kernels, we should provide reasonably good code, avoiding loop overhead and addition latencies. This code implements a 4x manual unrolling of the outer loop in the matrix-vector product with the respective reminder loops, and implements the option to create better code for unit-stride array access. In my tests, this PR gives a speedup of 1.6-1.8x for dim=3, degree={2,3} of the simplex matrix-free operator evaluation.

The code is still not optimal, because the simplices make a matrix-vector product, whereas it would be better to perform matrix-matrix multiplications. More precisely, one should combine 2 or 3 cell batches in order to amortize the load to matrix_ptr[0], as the current code is bottlenecked by the load to the matrix, and to hide the latency of the chained additions that gets clearly visible on my AMD systems with dim=3,degree=3. I have to reason more about what the best strategy could be, and would be happy to discuss options we have.

FYI @dominiktassilostill @nfehn.