FlatGFA: Optimize GFA parsing a bit

[sampsyo]

A bunch of little optimizations guided by some profiling, all for the parsing part of polbin.

I used two human pangenome GFAs to measure stuff. Measured on havarti (reporting times to convert GFA -> FlatGFA):

	chr22	chr8
original GFA size	2.4 GB	3.9 GB
FlatGA size	1.5 GB	2.1 GB
before time	28s	49s
after time	13s	18s

So that's a 2.2x and 2.7x speedup for the two input graphs, respectively.

Optimizations included:

• Getting rid of some collects to avoid allocating vectors.
• Replacing usize IDs with u32 IDs.
• The big one: optimizing for the (apparently common) case when segment names are sequential numbers, avoiding a hash table that was previously required to look up IDs by name.

Next steps would be:

• Roll my own (regex-free) GFA parser.
• Avoid the memcpy stage by pre-allocating big slabs of memory and parsing directly into there. Requires estimating the sizes of things, which seems hard?
• Something about how weirdly large the "path steps" parser looms in the time profile??