Ask HN: Heavy computation setup for Python?

[gavribirnbaum]

I'm running some DFT calculations at home, and they take way too long to run on my computer, I was looking for a pleasant and cheap way to develop these models while also speeding up the computation speed. Open to getting servers, etc, but would love some direction. Thanks!

[indoorskier]

I am obviously biased as one of the maintainers, but this is exactly the kind of thing we built Meadowrun for!

See https://meadowrun.io

It takes your local code and environment (we support pip, poetry and conda) and runs python code on AWS or Azure (though Azure might have some rough edges still). You can specify what kind of machine you want based on cpu/memory etc, no need to deal with weird instance names. You can get cheap spot instances etc.

[fastneutron]

I support some users running DFT, and I have a few questions: What’s your current setup? How big are the models? Which DFT code are you running; VASP, QE, something else? How long are your runs currently taking vs. how long do you want them to be?

(Edited for an autocorrect hiccup)

[gavribirnbaum]

I'm currently running things locally on my MacBook Pro. The models aren't too big, just a few atoms for now as I'm still testing things. But the optimization codes runs for a couple of hours, and I wish it went down to less than a half hour. I am running GPAW.

[mattbillenstein]

Have you tried spot instances on AWS? Fire up a box for a few hours, then spin it down when you aren't using it?