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General updates

  • JW – Thanks for quick fix to CPU platform. I’m waiting for conda packages to come online so I can test again.

  • JW – I worked a bit with Richard Gowers (head of OpenFE) to try writing a writing a more flexible PDB loader (one which can be taught about more residues). Results from hackathon: https://github.com/richardjgowers/dasPDB/. It seems like some big tradeoffs are

    • Should we use atom/residue names exclusively to find chemical templates? Or can we use elements+bonds (detected by distance) to find templates?

    • PE – Neither approach is really reliable.

      • Using names is bad because lots of files not from RCSB use nonstandard names. And if you do anyhting other than standard residues then all bets are off.

      • Using elements is hard because often the element column isn’t filled in, or contains info other than the actual element. Also bond detection by distance is unreliable.

    • JW – There’s also the MDAnalysis magic elements+connections → formal charge + bond order guesser

      • PE – This will fail when

        • explicit Hs may be missing

        • Ions that could have multiple charges (technically possible to put in a PDB file, but very rarely used in practice)

      • JW – We also just excluded all radicals from OpenFF toolkit. This may make the MDAnalysis guesser feasible.

      • PE – You’ll also need explicit elements and no missing atoms

      • JW – PE, would you be interested in following/joining this work?

        • PE – Yes, please loop me into these efforts. I’d like to follow along but won’t commit effort until I know more.

  • PE – When importing openff-toolkit, I get the advertisement for OE. I’d like that to go away. Would I cause any trouble by opening a PR to remove that?

    • MT – We actually should have jut removed that in the most recent release. https://github.com/openforcefield/openff-toolkit/pull/1426

    • JW – PE, if you reinstall, could you verify this goes away? This should have been fixed in last week’s release (0.11.3)

    • MT - tested in one of my envs and this is fine locally:

      • Code Block
        (openff-interchange-env) [forcebalance] conda list | grep openeye | wc -l                                                             13:08:38  ☁  fix-installation ☂
               0
        (openff-interchange-env) [forcebalance] python                                                                                        13:08:44  ☁  fix-installation ☂
        Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:00:52)
        [Clang 13.0.1 ] on darwin
        Type "help", "copyright", "credits" or "license" for more information.
        >>> from openff.toolkit import __version__
        >>> __version__
        '0.11.3'
        >>>
  • MT – Picking a platform - A lot of our code explicitly requests Reference, what’s the automatic option?

    • PE – It picks the fastest available, where speed is hard coded as Reference < CPU < OpenCL < CUDA.

    • MT – Relative performance of Reference and CPU?

    • PE – About ~10x, though for very small systems reference can actually be the fastest. Depends a lot between CPUs as well (n cores is a big contributor).

    • MT – For us it’s mostly doing a large number of single points, with just a few simulations.



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