The current implementation for computing relative block frequencies does

not handle correctly control-flow graphs containing irreducible loops. This

results in suboptimally generated binaries, whose perf can be up to 5%

worse than optimal.

To resolve the problem, we apply a post-processing step, which iteratively

updates block frequencies based on the frequencies of their predesessors.

This corresponds to finding the stationary point of the Markov chain by

an iterative method aka "PageRank computation". The algorithm takes at

most O(|E| * IterativeBFIMaxIterations) steps but typically converges faster.

It is turned on by passing option `use-iterative-bfi-inference`

and applied only for functions containing profile data and irreducible loops.

Tested on SPEC06/17, where it is helping to get correct profile counts for one of

the binaries (403.gcc). In prod binaries, we've seen a speedup of up to 2%-5%

for binaries containing functions with hot irreducible loops.