add (performant) abstraction over semilattices

[hochgi]

I describe an aspect of the problem in a blog post:
https://blog.hochgi.com/2019/01/fp-ish-patterns.html?view=classic

In general, given a "join" function that is commutative and associative, we can optimize computation by re-ordering the application of that function over a sequence of elements.

here's an example to clarify what I mean:

def foo[A](as: Seq[A])(f: (A,A) => A): A 

This can obviously be implemented as a.reduce(f), but it means the order of computation cannot be changed. Think about the matrix chain multiplication problem for instance.

(actually, matrix multiplication is associative, but not commutative, so not a 1:1 example, but you get the idea, and maybe there is a way to define an abstraction for that as well)

disclaimer: I'm not very familiar with scalaz. this issue was suggested to me by @jdegoes, and I will be happy to provide any further details or a more detailed example.

[iravid]

Closing as this is out-of-scope for ZIO