[Qem]

> There is also a layer of friction between doing the computations and then analysing the logs that comp chemistry programs spit out. If you want to visualise orbitals or look at the outputs of your simulations, it's really awkward to run Python whilst being in the cluster, and the cluster has no GUI display.

By the description it appears computational chemistry is stuck in batch processing era. They are yet to discover their equivalent to REPL tight feedback loop workflow.

[sseagull]

I’m a computational chemist who has been working on this kind of stuff for a while, and I will say it’s just a weird field. The overall issue is that it’s still very academic and very very fragmented. People have tried to make businesses out of this stuff but it has rarely worked, and there isn’t enough money/funding to sustain the level of work needed to really advance the field in that way. Especially now that government funding is drying up and business are reluctant to spend on fundamental research like this.

[StableAlkyne]

> People have tried to make businesses out of this stuff but it has rarely worked

The only two startups I'm aware of who have managed to make compchem-as-a-service a viable business are Mat3ra and Materials Square. Both are a little rough in their own ways (to be expected from startups), but it's still interesting to see some of this move beyond university clusters.

[theideaofcoffee]

Like another comment has mentioned, the field doesn't really lend itself to quick iterating jobs and loops and favors the long batch processes, for several reasons. Oftentimes, a structure calculation or optimization, if run using a "cheap" (computationally-speaking, say a semi-empirical or molecular mechanical) model, those can be done in seconds or minutes, sure. But for calculations that wish to approach or approximate characteristics of a structure seen in the real world, those can takes days or sometimes weeks, depending on the level of theory. There's also the interaction between different programs, or "codes" as they're called, feeding the output of one into another program to look at different phenomena, which is ideal for a batch system, especially if you are exploring a set of related structures or functionalities.

You will see a lot of similar procedures in, say, AI model training and refinement. Those depend on batch jobs as well, pretty heavily. So the batch process isn't really restricted to the weirdness of academia. My source there is actually working on the systems doing training for frontier models...

(Please forgive some of my hand-waviness or vagueness, it's been nearly 20 years since I last touched a lot of this).

[StableAlkyne]

> it appears computational chemistry is stuck in batch processing era

I wouldn't call it "stuck," since it's one of the few fields where batch processing makes sense.

You generally run your jobs on a supercomputer that's being shared by a few hundred other people. You need a scheduling system to allocate resources (e.g., 5 jobs requesting 10 nodes for 8 hours, 1000 jobs requesting 0.5 node for 5 minutes, etc).

It's hard to tighten the workflow when the average calculation takes 2-3 hours of time.

[selimthegrim]

You can fly by wire SLURM via Claude Code and bash fairly easily or run MATLAB batch over ssh tunnel etc