Dec 28, 2015
@jandom sorry didn't see this until now. Since the
Topology is a collection of
numpy arrays instead of a list of
Atom objects, it should perform better for many smaller systems, too, and each one also has a smaller memory footprint since we only have as many attributes as we need, no duplication of data, etc.. We already see that we get a decent speedup on parsing a GRO file with this new scheme, but we also omitted guessing from it, too, so perhaps it's not a fair comparison.
Does that kinda answer your question?
Jul 5, 2016
The notebook says that the benchmark system are not available but we recently put them on figshare (as also mentioned in the updated README for the vesicle_library):
A set of large vesicle systems, ranging in size from 1.75 M to 10 M particles are made available under doi:10.6084/m9.figshare.3406708.
Mar 16, 2017
@dotsdl please fix the notebook as it holds up MDAnalysis/MDAnalysis.github.io#41 (see also MDAnalysis/MDAnalysis.github.io#41 (comment) )
- fix availability of vesicle library
- remove stupid json warnings
Wow, this looks awesome! This benchmark is largely a mode where "read-in one, big system", how is this expected to perform in "read in many, small systems"?