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112 points cl3misch | 1 comments | | HN request time: 0.351s | source
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aa-jv ◴[] No.44385929[source]
Very interesting .. I was recently tasked with getting a bespoke AI/ML environment ready to ship/deploy to, what can only be considered, foreign environments .. and this has proven to be quite a hassle, because, of course: python.

So I guess Apptainer is the solution to this use case - anyone had any experience with using it to bundle up an AI/ML application for redistribution? Thoughts/tips?

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SirHumphrey ◴[] No.44385965[source]
I did start to use them for AI development on the HPC I have access to and it worked well (GPU pass-through basically automatically, the performace seemed basically the same) - but I mostly use them because I do not want to argue with administrators anymore that it's probably time they update Cuda 11.7 (as well as python 3.6) - the only version of Cuda currently installed on the cluster.
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aa-jv ◴[] No.44386135[source]
Ah, right. So, no matter what container comes along to solve this problem, there's still the BOFH factor to deal with ..

Curious though, how are you doing this work without admin privs?

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SirHumphrey ◴[] No.44386850[source]
It's a bit annoying, but you can install conda without admin privileges and apptainer was installed for compliance with some EuroHPC project and luckily made accessible to all users. The container allows me to have an environment where I have "root" access and can install software.

The most annoying thing is not the lack of privileges, but that the compute nodes do not have internet access (because "security") beside connecting to the headnode, so there is the whole song and dance of running the container (or installing conda packages) on the headnode so I can download everything I need, then saving the state and running them on the compute node.

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1. aa-jv ◴[] No.44394406[source]
Seems to me that you might benefit from containerizing your apptainer development environment. ;)

/ducks