In real heterogenous-workload production clusters, every available machine likely has several VMs scheduled on it if the cluster isn't idle. There is never a full machine that's free unless some special effort has been taken to make it so.
To make things more complicated, a long-lived cluster is going to be made up of different classes of machines, from different CPU micro-architecture, so 'single machine' is overly constraining. Eg it's not interesting that a job with a 4 MiB requirement can always run if your job needs 32 GiB.
"Rather than making your computation go faster, the systems introduce substantial overheads which can require large compute clusters just to bring under control.
In many cases, you’d be better off running the same computation on your laptop."
My limited experience fits this in that a bit of smarts on a single box beats a bunch of boxes.
(the link is a very good read BTW)
Of course, for a batch job with a runtime under 11 minutes, that probably doesn't really matter too much. Just don't generalize that too much.
