Be ready to run many jobs in parallel

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
python
Domain
distributed-systems

Research direction

Start by locating the code that checks for finished reactant log files and launches calculations on XSEDE. Examine how concurrent jobs share reactants and log-file directories, then define tests or a reproducible scenario with many parallel reactions. Done should mean shared reactants are calculated once without competing writes.

Written by the indexing model from the issue text.

Description

For example, if you start 1000 reactions at once (on XSEDE) and 100 of them have a reactant in common, they will each ask themselves "do I have finished log files for this reactant?" and decide "no, I don't, so let me start calculating it". Then you are calculating the same reactant 100 times, probably fighting over saving the log files in the same folder.

This is the sort of thing we need to anticipate and avoid.

We should do something like a "HAZOP" of our code. Think about "too much flow?" etc. at each point. or "what if...".

Dominant language
Python
Stars
51
Forks
19
No merged PRs in 30d

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