ENH: add `mdot`: fast dot with multiple arguments.

This is not ready to be merged!

`mdot` makes it easy to chain `dot`. Think of `mdot` as this:

    def mdot(*args): return reduce(np.dot, args)

However, `mdot` uses the fact that matrix multiplication is associative and
finds the optimal order of multiplications with dynamic programing before
doing the mutiplication. This can speed up the multiplication quite a bit.

The algorithm follows:
Cormen, "Introduction to Algorithms", Chapter 15.2, p. 370-378

Note: currently `mdot` only works with arrays which have `ndim == 2` to avoid
ambiguities of `dot`. Also see the discussion in #4311.

TODO:
- [x] Decide if `ndim != 2` should be ok
- [x] Add unittests
- [x] decide on name. possible names are:
  - `mdot`: think "multi dot"
  - `multidot`: as above :)
  - `multi_dot`: as above :)
  - `chain_dot`
  - `fdot`: think "fast dot" (should the parameter optimize be optional then? I don't think so.)
  - `ddot`: think "multiple d for multiple dot"
  - `cdot`: think "chain dot"
  - `odot`: think "optimal do

If you do `multi_dot(a, b, c, d, e, f, g, h)` and it is optimized as `((a*b)*(c*d))*((e*f)*(g*h))`, you are going to have to hold more temporary intermediate arrays (I count 4) than the 2 needed for doing the straightforward `((((((a*b)*c)*d)*e)*f)*g)*h`. Since the optimized order is probably getting rid of the larger dimensions earlier, I am not sure that the total size of those more arrays is going to exceed that of the fewer.