Faster distance computation

[Liblor]

Hi

I am using parts of AflGo for my master thesis. Since the distance computation was a bit slow for my use-case I rewrote it in C++. This version acts as drop-in replacement for distance.py. Furthermore, I replaced the genDistance.sh with a python script which calls the distance computation in parallel.
These modifications result in a significant speed up!

Summary of optimizations:

• Use C++ instead of python
• Use BFS instead of Dijkstra as graph is unweighted
• Parallelize computation

[mboehme]

Thanks for your contribution @Liblor! LGTM.
@strongcourage Can you also have a quick look?

[mboehme]

Thanks again @Liblor! As spoken separately, let us know if you have some updates/experience on porting AFLGo to LLVM 11 (or higher).

[Liblor]

Addendum:

As promised @strongcourage, I timed the distance computation of xmllint and
cxxfilt.

	genDistance.sh	gen_distance_fast.py	rough speed up
xmllint	85min 39.8s	28.6s	~180x
cxxfilt	17min 48.2s	15.1s	~71x

Machine: i7-10700 CPU @ 2.90GHz, RAM 32GB (Dell OptiPlex 7080)
Distro: Ubuntu 18.04.5 LTS

Note: This is not a scientific measurement. I ran genDistance.sh only
once and gen_distance_fast.py three times (reported median). Also I didn't
disable intel turbo boost and ignored other best practices. However, I didn't
do any other work on the machine during the computation. This should only
act as an approximation to see the rough magnitude of the improvement :)

[strongcourage]

Hi @Liblor,
Thank you for this table, it looks great :)

[mboehme]

Nice work! Thanks again @Liblor.