I’ve learned so much setting up a pi cluster. There is something so cool about seeing code run across different pieces of hardware.

The point was you don't need to wait for 8 Pis to become available when most people can get going straight away with what they already have.

If you want to learn physical networking or really need to "see" things happening on physically separate machines just get a free old PC from gumtree or something.

> Old quad core won't have all the virtualisation extensions.

Intel's first quad core was Kentsfield in 2006. It supports VT-x. AMD's first quad core likewise supports AMD-V. The newer virtualization extensions mostly just improve performance a little or do things you probably won't use anyway like SR-IOV.

Ivy Bridge is 13 years old today. You need to do the the things to buy something older than that in 2025.

Virtualization existed long before virtualization instructions. Not strictly necessary.

An old Xeon then.

Newer CPUs have significantly better performance per watt under load, essentially by being a lot faster while using a similar amount of power. Idle CPU power consumption hasn't changed much in 10+ years simply because by that point it was already a single digit number of watts.

The thing that matters more than the CPU for idle power consumption is how efficient the system's power supply is under light loads. The variance between them is large and newer power supplies aren't all inherently better at it.

If the point is a multi-tasking sandbox, not heavy/sustained data-crunching, those old CPU's w/ boosting turned off or a mild underclock/undervolt (or an L spec which comes iwth that out of the box) really aren't any more power hungry than a newer Ryzen unless you intend on running whatever you buy at high load for long times. Yeah, on paper it still could be a double digit percentage difference, but in reality we're talking a difference of 10W or 20W if you're not running stuff above 50% load for sustained periods.

Again, lots of variables there and it really depends on how heavily you intend to use/rely on that sandbox as to what's the better play. Regional pricing also comes into it.

I don't know, but when I was playing with finite difference code as an undergrad in Physics, all of the docs I could find (it was a while ago, though) assumed that I was going to use MPI to run a distributed workload across the university's supercomputer. My needs were less, so I just ran my Boost.Thread code on the four cores of one node.

What if you had a single server with a zillion cores in it? Maybe you could take some 15 year old MPI code and run it locally -- it'd be like a mini supercomputer with an impossibly fast network.

I’m not thinking of one code in particular. Just, observing that in the multi-chiplet, even inside a CPU package we’re already talking over a sort of little internal network anyway. Might as well use code that was designed to run on a network, right?