Add benchmark suite

We should track method performance using a benchmark suite like @alimanfoo mentioned in https://github.com/pystatgen/sgkit/pull/36#issuecomment-658893949.

It would be ideal if this ran as a part of the build, but timings gathered that way are probably not very reliable. Apparently integration of ASV suites in builds is usually just to make sure they work: https://github.com/astropy/astropy/issues/6149. Presumably we should have a separate, scheduled process that runs on dedicated resources in order to benchmark accurately.

As @hammer mentions in https://github.com/related-sciences/gwas-analysis/issues/10, https://github.com/ornl-oxford/genben could also be a helpful resource (scikit-allel benchmarks).

Ideas for benchmarking:

• sgkit.utils.max_str_len (see https://github.com/pystatgen/sgkit/pull/314#discussion_r502590724)

[hammer]

Conbench from Ursa Labs could be useful for us: https://ursalabs.org/blog/announcing-conbench. cc @arunkk09 and @LiangdeLI

[ravwojdyla]

Just wanna drop ann-benchmarks as an inspiration. From readme:

Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem, but so far there has not been a lot of empirical attempts at comparing approaches in an objective way. This project contains some tools to benchmark various implementations of approximate nearest neighbor (ANN) search for different metrics. We have pregenerated datasets (in HDF5) formats and we also have Docker containers for each algorithm. There’s a test suite that makes sure every algorithm works.