Updates from MolSSI | Ben | BP: upgraded public QCA with 0.15.7, went very smoothly BP: do still have traffic routing through backup host BP: working on improvements in next failed calculation history; necessary for in-server error cycling; also doing tons of renaming to get consistency in verbiage in the codebase (e.g. datasets instead of alternatively collections and datasets) Tentatively looking for Feb release
BP: saw new QCFractal issues raised by @Lily Wang ; many of these are going to be addressed in next DD – Highmemory jobs fell into a weird state: following tasks stuck in RUNNING state: ['12669181', '12669182', '12669211', '12669338', '12669339', '12669341'] result ids: ['76498626', '76498467', '76498496', '76498466', '76498624', '76498623'] BP – Updated from my end – These should be fixed now DD – How does this happen? Race condition in the manager? BP – Yeah. It can happen when a task gets assigned to a manager, but the manager shuts down at the same time. In the next branch, there will be a locking of the manager during this time.
PB – Question regarding B97 fix – Does this work for existing datasets, or only new submissions. BP – This should work for existing datasets. Though we may need to do recomputations. You may need to call .compute() on those again – I’m pretty sure this will work. DD – That makes sense. I’ll push PR #227 through the submission pipeline again. PB – For new submissions, will it split into two calculations? Like into functional and dispersion? BP – This won’t split those, since psi4 doesn’t understand the functional part. PB – I still see two sets of records for the new submission #239
BP – I think this is due to using an old qcportal. Should be fixed after upgrade – Should have 0.15.7. This problem should be entirely local. PB – Would this have been a problem if I also used an old qcsubmit? BP + DD - I don’t think so. It shouldn’t be necessary to rerun things for the new submissions.
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New submissions |  | TorsionNet Solvated amino acids PB – these datasets should help OpenFF; we have had complaints that training and benchmarking are done with same QM method/basis; these datasets will give us greater variety to test against JW – had seen with pubchem set1, looked like we have funny conformer counting PB – was related to an issue with inchi keys JW – saw that there were an average of 50 conformers generated per molecule; seemed suspicious there are more than 1k unique graphs in this dataset? PB – yes, and each one has 50 conformers, one has exactly 100 JW – oh, I was under the impression we were generating conformers! PB – no, Peter generated his own conformers specifically for these molecule
DD – There was just a comment that the dataset includes I
DD – How should I proceed with the SPICE dataset? Should we wait to see success on SPICE before we submit the others
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