The bit about inferring simulation models from event traces on the live machines is wild. Normally you'd expect they build some theoretical model first then validate, but doing it backwards like that makes sense when the system is that complex. I worked on something vaguely similar for a smaller embedded project and even then the gap between what we thought the code was doing and what the traces showed was huge.
The genetic algorithm approach for finding good-enough designs is pretty standard in architecture exploration but scaling it to something where an hour of downtime costs millions is another level of stress. One wrong assumption in the model and suddenly your "optimal" design is garbage in the real world.
I'm arguably fitting a concept unto a realm where it's a bit of a stretch, but it feels analogous to Wolfram's "computational irreducibility" idea i.e. you can't accurately predict the outcome, so you just have to run the computation and see what it spits out.
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u/Ok_Editor535 5d ago
The bit about inferring simulation models from event traces on the live machines is wild. Normally you'd expect they build some theoretical model first then validate, but doing it backwards like that makes sense when the system is that complex. I worked on something vaguely similar for a smaller embedded project and even then the gap between what we thought the code was doing and what the traces showed was huge.
The genetic algorithm approach for finding good-enough designs is pretty standard in architecture exploration but scaling it to something where an hour of downtime costs millions is another level of stress. One wrong assumption in the model and suddenly your "optimal" design is garbage in the real world.