Implements a profile synthesis algorithm based on the classic Wu-Larus
paper (Static branch frequency and program profile analysis, Micro-27,
1994), with a simple set of heuristics.

First step is construction of a depth-first spanning tree (DFST) for the
flowgraph, and corresponding reverse postorder (RPO). Together these drive
loop recognition; currently we only recognize reducible loops. We use DFST
(non-) ancestry as a proxy for (non-) domination: the dominator of a node
is required to be a DFST ancestor. So no explicit dominance computation is
needed. Irreducible loops are noted but ignored. Loop features like entry,
back, and exit edges, body sets, and nesting are computed and saved.

Next step is assignment of edge likelihoods. Here we use some simple local
heuristics based on loop structure, returns, and throws. A final heuristic
gives slight preference to conditional branches that fall through to the
next IL offset.

After that we use loop nesting to compute the "cyclic probability" $cp$ for
each loop, working inner to outer in loops and RPO within loops. $cp$ summarizes
the effect of flow through the loop and around loop back edges. We cap $cp$ at
no more than 1000. When finding $cp$ for outer loops we use $cp$ for inner
loops.

Once all $cp$ values are known, we assign "external" input weights to method
and EH entry points, and then a final RPO walk computes the expected weight
of each block (and, via edge likelihoods, each edge).

We use the existing DFS code to build the DFST and the RPO, augmented by
some fixes to ensure all blocks (even ones in isolated cycles) get numbered.

This initial version is intended to establish the right functionality, enable
wider correctness testing, and to provide a foundation for refinement of the
heuristics. It is not yet as efficient as it could be.

The loop recognition and recording done here overlaps with similar code
elsewhere in the JIT. The version here is structural and not sensitive to IL
patterns, so is arguably more general and I believe a good deal simpler than
the lexically driven recognition we use for the current loop optimizer.
I aspire to reconcile this somehow in future work.

All this is disabled by default; a new config option either enables using
synthesis to set block weights for all root methods or just those without PGO
data.

Synthesis for inlinees is not yet enabled; progress here is blocked by dotnet#82755.