Sentence-level parallelism

[rht]

I was trying to reproduce the result of https://github.com/Futrell/cliqs/blob/1c72b064f9048f9344ca88c90d6dface616d7ee4/run_mindep.py#L49.

I found that pooling did result in a 2x speed up of the run.

Without parallel:

python run_mindep.py run en fr  866.40s user 0.48s system 99% cpu 14:28.04 total
python run_mindep.py run en fr  893.17s user 0.53s system 99% cpu 14:55.14 total
python run_mindep.py run en fr  905.34s user 0.56s system 99% cpu 15:08.00 total

With parallel (pmap):

python run_mindep.py run en fr  404.78s user 13.91s system 48% cpu 14:23.18 total
python run_mindep.py run en fr  410.19s user 14.25s system 47% cpu 15:01.91 total
python run_mindep.py run en fr  418.29s user 14.64s system 54% cpu 13:09.16 total

This was ran on "Intel(R) Core(TM) i5-4200U CPU @ 1.60GHz", quadcore. I think the run could be ~an order of magnitude faster by inserting several numba @jits to deptransform/depgraph. So far I had tested with @jit-ing gen_row but didn't observe any speed up.

[Futrell]

It's definitely very possible to make this faster with numba. It's currently set up to work with pypy, and that's what I've been using when speed becomes a bottleneck. It's possible that numba would provide a better speed/simplicity tradeoff but I haven't felt hindered by speed as it is.