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Hi All, Is There A Way To Schedule The Tasks From The Queue Onto The Gpu Instances Based On Factors Such As Gpu Utilisation, Number Of Cpu Cores Present, Free Memory Or Custom Parameters Such As Priority Of The Task, Estimated Time Etc?

I can definitely see your point from the "DevOps" perspective, but from the user perspective it put the "liability" on me to "optimize" the resource, which to me sounds a bit much to put on my tiny shoulders, I just have a general knowledge on what I need. For example lots of CPUs (because I know my process scales well with more cpus), or large memory (because I have an entire dataset in memory). Personally (and really only my personal perspective), I'd rather have the option to select from a limited list of options (which can amount to a list of queues).
Now from the DevOps perspective that means spinning multiple k8s glues (with diff template YAML each one) and connect each job template to a different queue, while naming the queues with the actual resources.
for example the following queues are quite self explanatory:
24cpu_128gb_hd1tb, 48cpu_128gb_hd1tb, 4v100_32cpu_256gb_hd2tb
This means that as a DevOps I can put a max limit per queue/resource and always hav ethe ability to add more (just my 2 cents)

Posted 3 years ago
0 Answers
3 years ago
one year ago